{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparation \n",
    "## Append to path and import\n",
    "In case gumpy is not installed as package, you may have to specify the path to the gumpy directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Once deleted, variables cannot be recovered. Proceed (y/[n])? y\n"
     ]
    }
   ],
   "source": [
    "%reset\n",
    "%matplotlib inline\n",
    "\n",
    "import sys, os, os.path\n",
    "sys.path.append('../../../gumpy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## import gumpy\n",
    "This may take a while, as gumpy as several dependencies that will be loaded automatically"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import gumpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import data\n",
    "To import data, you have to specify the directory in which your data is stored in. For the example given here, the data is in the subfolder ``../EEG-Data/Graz_data/data``. \n",
    "Then, one of the classes that subclass from ``dataset`` can be used to load the data. In the example, we will use the GrazB dataset, for which ``gumpy`` already includes a corresponding class. If you have different data, simply subclass from ``gumpy.dataset.Dataset``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gumpy.data.graz.GrazB at 0x7f5aee8fc630>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First specify the location of the data and some \n",
    "# identifier that is exposed by the dataset (e.g. subject)\n",
    "\n",
    "data_base_dir = '../../../Data'\n",
    "\n",
    "grazb_base_dir = os.path.join(data_base_dir, 'Graz')\n",
    "subject = 'B01'\n",
    "\n",
    "# The next line first initializes the data structure. \n",
    "# Note that this does not yet load the data! In custom implementations\n",
    "# of a dataset, this should be used to prepare file transfers, \n",
    "# for instance check if all files are available, etc.\n",
    "grazb_data = gumpy.data.GrazB(grazb_base_dir, subject)\n",
    "\n",
    "# Finally, load the dataset\n",
    "grazb_data.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The abstract class allows to print some information about the contained data. This is a commodity function that allows quick inspection of the data as long as all necessary fields are provided in the subclassed variant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data identification: GrazB-B01\n",
      "EEG-data shape: (1626266, 3)\n",
      "Trials data shape:  (324,)\n",
      "Labels shape:  (324,)\n",
      "Total length of single trial:  8\n",
      "Sampling frequency of EEG data: 250\n",
      "Interval for motor imagery in trial:  [4, 7]\n",
      "Classes possible:  [0 1]\n"
     ]
    }
   ],
   "source": [
    "grazb_data.print_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Postprocess data\n",
    "Usually it is necessary to postprocess the raw data before you can properly use it. ``gumpy`` provides several methods to easily do so, or provides implementations that can be adapted to your needs.\n",
    "\n",
    "Most methods internally use other Python toolkits, for instance ``sklearn``, which is heavily used throughout ``gumpy``. Thereby, it is easy to extend ``gumpy`` with custom filters. In addition, we expect users to have to manipulate the raw data directly as shown in the following example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Common average re-referencing the data  to Cz\n",
    "Some data is required to be re-referenced to a certain electrode. Because this may depend on your dataset, there is no common function provided by ``gumpy`` to do so. However and if sub-classed according to the documentation, you can access the raw-data directly as in the following example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "if 0:\n",
    "    grazb_data.raw_data[:, 0] -= 2 * grazb_data.raw_data[:, 1]\n",
    "    grazb_data.raw_data[:, 2] -= 2 * grazb_data.raw_data[:, 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Notch and Band-Pass Filters\n",
    "``gumpy`` ships with several filters already implemented. They accept either raw data to be filtered, or a subclass of ``Dataset``. In the latter case, ``gumpy`` will automatically convert all channels using parameters extracted from the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# this returns a butter-bandpass filtered version of the entire dataset\n",
    "btr_data = gumpy.signal.butter_bandpass(grazb_data, lo=2, hi=60)\n",
    "\n",
    "# it is also possible to use filters on individual electrodes using \n",
    "# the .raw_data field of a dataset. The example here will remove a certain\n",
    "# from a single electrode using a Notch filter. This example also demonstrates\n",
    "# that parameters will be forwarded to the internal call to the filter, in this\n",
    "# case the scipy implementation iirnotch (Note that iirnotch is only available\n",
    "# in recent versions of scipy, and thus disabled in this example by default)\n",
    "\n",
    "# frequency to be removed from the signal\n",
    "if False:\n",
    "    f0 = 50.0 \n",
    "    # quality factor\n",
    "    Q = 50.0  \n",
    "    # get the cutoff frequency\n",
    "    w0 = f0/(grazb_data.sampling_freq/2) \n",
    "    # apply the notch filter\n",
    "    btr_data = gumpy.signal.notch(btr_data.raw_data[:, 0], w0, Q)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Normalization\n",
    "Many datasets require normalization. ``gumpy`` provides functions to compute normalization either using a mean computation or via min/max computation. As with the filters, this function accepts either an instance of ``Dataset``, or raw_data. In fact, it can be used for postprocessing any row-wise data in a numpy matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized Data:\n",
      "  Mean    = -0.000\n",
      "  Min     = -21.830\n",
      "  Max     = 14.876\n",
      "  Std.Dev = 1.000\n"
     ]
    }
   ],
   "source": [
    "# normalize the data first\n",
    "norm_data = gumpy.signal.normalize(btr_data, 'mean_std')\n",
    "# let's see some statistics\n",
    "print(\"\"\"Normalized Data:\n",
    "  Mean    = {:.3f}\n",
    "  Min     = {:.3f}\n",
    "  Max     = {:.3f}\n",
    "  Std.Dev = {:.3f}\"\"\".format(\n",
    "  np.nanmean(norm_data),np.nanmin(norm_data),np.nanmax(norm_data),np.nanstd(norm_data)\n",
    "))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting and Feature Extraction\n",
    "\n",
    "Certainly you wish to plot results. ``gumpy`` provides several functions that show how to implement visualizations. For this purpose it heavily relies on ``matplotlib``, ``pandas``, and ``seaborn``. The following examples will show several of the implemented signal processing methods as well as their corresponding plotting functions. Moreover, the examples will show you how to extract features\n",
    "\n",
    "That said, let's start with a simple visualization where we access the filtered data from above to show you how to access the data and plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5ae516ceb8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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TV3NsJB8hIgBTWmcnC3IVHV/4pDfdek8eUKv1DgT9omjJJCN5o3aeXmrg339R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EzjVyqloS2hkkq5HJLMKgK3X7sZ3/jRMdx/5+4F3Xepo91jecf+O/Gd53+Aw+aVSBsRedcvIayV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\nx4gRI8YaQkzUY8SIEWMN4f8HiK9ds2p0LZwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b25a558d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "# Plot after filtering with a butter bandpass (ignore normalization)\n",
    "plt.figure()\n",
    "plt.clf()\n",
    "plt.plot(btr_data[grazb_data.trials[0]: grazb_data.trials[1], 0], label='C3')\n",
    "plt.plot(btr_data[grazb_data.trials[0]: grazb_data.trials[1], 1], alpha=0.7, label='C4')\n",
    "plt.plot(btr_data[grazb_data.trials[0]: grazb_data.trials[1], 2], alpha=0.7, label='Cz')\n",
    "plt.legend()\n",
    "plt.title(\" Filtered Data\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EEG band visualization\n",
    "Using ``gumpy``'s filters and the provided method, it is easy to filter and subsequently plot the  EEG bands of a trial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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l4ovHqSdt2bGzftrXs9hvcttT3+C6yav5xe995Vm361zAbQVZhcWxidqg1AJQ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braI3S1R+hqj17Stc2gb3s+MH8I37UOKCocA7zfos3GFvs/L65/ZPcmtQ6CIOgA2231ju11wCeS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b251b4e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pKqiUX9g2uYFjyEJrs02fGn+WA1O1w3kT+XFm8s2TuBVsUfpeAIbTo2TtPE6+\nwBXP/ZTL993ekhzVnBpP8eNHTyzo2KVioQOqG4A7gHeZpnl31e5uYJ9hGBcBaeDncAdfVwave5bK\nWkzMZtkxl6G7ySF+hJDMpQvIgWNYU1OobW1oHc1dF4vBUd2PXDg2LDB1lmZbOJrOvmNTzCTzXLC1\np+6Hv+nkPlJanEfuz9CzqZ/XvHRXw3Or3sBQxsqyd2I/MS3GNRuunJd8RVF2HXvMt3Fep1gW8gWH\nHz08wIsu2sD2jfW7xeOZCU54vT0XV3gxPcXMAz9Fz88vk+BX938bXdW4cfvP0RFpZ22dyS55p0C9\nYefRn95O588pxM8/f151t4qes5B3/Zh0JE4u75DOVi+kMT/GMxP0tVWtQ1Dds3Qcpm75IV3XvKil\nc+acfN33aC6foC9WP0BCInE8fSGERFUVCo7FRHaCLR1bANDtPC99ZopD29dAleV+76mHuGr95fTE\ngjVMrtlU2GVmoZb7B4A+4MOGYdzn/fdWwzDeYZrmnLf/XuBB4HnTNH+8RPK2zFTCVZhD09kKJdfM\n0plJ5phO5EikC4x//SuMfvFzgeWydhbLWdzLbit5LLXsjnIKC3sZNNviyr23ccHhhwEYmkhx71ND\ndcoW6B85xI6TT7PhyTtw7mrh0VS5p5KF1LxlDLLG68Yir6DSN0/NMjyZ5gdN3F7fPXxrRSioVNze\ni8ymGx4nZaVx6giJ8OLdbeFw28CdfPvQD+se3ywU0Um11pUfTY/xuX1fYzwzUbFd2jZjX/0SqWee\nrpmpqS+yJ5m3nAq3oCNFzUSverOzc6fqBwJUnQBliXsvUla+gl3pPFfvH6kpd3D6MHecaDTfoPLa\nLMfi9uP31MwdWC4W6nN/D/CeBvu/CizDirbNyVsOo9OZ0kvVdvg5xr82yYbf/j2Ojya47ZHj3Jgv\nv7T1FIztCGxHolH78gkp+NLz36Qr2slvXfRrC5bV1iqV5EKnmEe87n1XqvkiEVpVg9SRmX+mwuqZ\neI2QQpB87FHsDVsalptof5p14gIUOlbUoNe0hY2rlNYFbRLulqtqsAuWQzbfulFwInGKLVaarkhw\n77FVt8z9g49gORZ7xp7lF3a+prTdmhjHnpnh5E/u4J5jOmK7Q0TX0HMW0czi8u0LIcmL2rTSFWG/\n9fIq1cnMaM/MkNz9BJ1XX1uTxmNesnnhx0FIXO3uKBZCafysgnLMlM9Tea2HZo9xbO4EA9MDvOOS\n36oZC1xUEPZSAAAgAElEQVRqzqpJTNM/vpWhe+6v8KHlLYfEiGutPHd0CtsWzKTKk2SElGQKtQ+w\nYAlOjSeZmqv1i9qez3khFmwjRJNc1fWQ8xj4DbJy5uu3nY86zJ84TnL3EyRv/X5tvb5Ps6DNMRpb\nfORsfmiQ1DPNJ5wU0X2pev/9O8+WQtkAkpkC33/gWJ1FUTzZF2I1zqMNPzRzlKlGaQ1aNAiKUmpK\nVUSa11BPp9LMqodI59xv5+I7D7LjyRMsSzfKf8/qLZxRb3A6lyXxyMOl1MEKoMxTRFs4nEoOMt0k\nBbOlJnHUxjOPi2HC7jdUM7hS0WOVU9O0z2Q49/HjjHz6P0uphZcrb9BZkVtmLpdASEn2yGGwbYRi\nI5FoMkLBchibybB2LoscOcX2gd2k5FTJjzmSnMB2BDHWViitosWVDLBe7GXKGbESy3wFKXchJdp8\nGoh5lBWW23BKIVg3MVC5s0aURShMj+LamO0XXdySZVRd1f1PD/GWGy7ATiS4/6kRTk7k+MH9R6Ct\nslxOnyKnzzAw3M85szki8fnI3FpZLW+z/uhE40KtDop7b7cICCAAyClzvGTP/Yyev56OgBDCVqbz\nt4wQ4EWF+Q0LIX3JNZtEcYlslqnsDGk72/I9kEAqn8YW7l3wpwiuVcuypVajqNyfOjTJvmPTVeay\nxHEkmrdNv+UudmVnKNiCgbyOtvtp0tOTZA/uRn3b26C3ce92vpzxyv3I7AD3H3yIF6+9mj7clryg\nuaPkmr22VG73v3+aNdk5cvqUZ+m6Fkx5wQpBvY7Mt+89wpW71nHB1l6ShRRz8xw8axWxwOnpiq9R\n2H7iacbWn0cuHjzIowR8NP4X0I+UkpPJwZqcMq3OvMsePUJhaNA7F2w/9Wzl+esojKVQI27mybJy\nd5JJpm//CT3Xv5zoho1167KFdP3QX/o8G9KSo7te7cZOVyn3dNRNODU2rtGbLdAdcz9kFEoTehbr\nCt65+wTt0xlPThl435tlFE1bGe46eT+JQqKmvJQ+beopsi1HJ135PXdV6RktoW6XUpSvxLtJjpCc\nGk/R0Rahv7etuTUrBd8+9AOklCQSAVFHAfImCknmCgnUFhwWsy1E2kBZud//3AC0V4mgVI01eX86\njiACHPnBbThKAb09y8mTh9i6xMr9jHfLFKfG7586iBD1w+jas8EPq+w7rf/2jkym+cljbj1fO/Ad\nbjlWDo+SUjL38EPkh5sn55dCkDt+HGkHW/714qSbofj6+eumTpQGVgPLBtyftHkw0DXz/NRBfjxw\nF8Op0YrtrX7n07fdQvq5vaSyVs1CHAJRYTldu3eIjeOVg4Mi17hL3IjqtTaTT+2hMDzE9K23VJar\nuu71A88y8ll3CUCt4EUx+RrP/qk0W0fK75JS6pZDwXYoWM0b6EYGoS3s0sBtLOWzLAOOyRcc0gcP\nkjmwv+75Hh/dw3BqtORK9FvuY1/4XKmnU8QRgoJdHgiVeP7pBtcjcEqhoe5vm4JavkeWLSrvs7+H\nWlTujusDT2ULRUEa1Fh2Zcym8nVXGgOYzs1iCwchJQXvfQvqebtjIbZXtWSmjr4IYjI7xWjno9hV\nLhxHyXF8rpzwraEpswzTWc945V7EtmxOjCVItDAIJKQsKZuyNVR96xVkC51Ra3KC1J4nmbz5W03r\nzZ88ydSPvh9YGyxCufs+FolAdZJ1JVcCHL7Ju24n/dzemu0T2XrZGVs34wq2YGI2y3jVJLWCPsN0\nboZcwcF2BH3JHJeabkz32HSGI/c9xshn/ovMoYWlJJKOw2x+rrS6juJ1TUS+bOUJKZnMjzPUdR85\nbRqBzZrhQ0jPlVS8TM3XrfmZg6NcdGySSFGJS9cFaAc+u/mbu/smD/Ckl6RK+r53//MUErJ5hxOj\nSUaPD5cW8QiievDbr2SddKpuPHmx2FR2msHUcN2MoBJJQZ8lr5WVYUFL4lA+r+0Icv7IG1mp3CW1\n7qJm6woXx6c2D0xxxcHauQAFx6FgCxKFJIOpYU4mB1teqalgOfNagrJe9Es6OsRdg/eQtjJIIUoJ\n5PwUf1XPlF0KznjlXnzpndLL41d09bEdETh7UyLJawlsJUten8ZWywNsQdbt1w/c3DCPd9rK8Nzk\nfhzhkB31hyfWnstpwS1jqSksNeU1PO45/ArbUtNYWpK8VmewKDAkEdLP7SV79EjFdtsW5encjU9R\nFyEqn4fAoaAmSvuC7ulMMs/RB5/AEbKhVVohkxAIy/fxOjbfOPg9vnv4FuxCHkV3PZDFXlMmZ/OZ\nHz3PPceeBGCqfS8jXQ8hfJk0ipIFGVWaZ1naaoq8Pk3aan1wPaj3lMgU+MnjJ5jLBYdWFu+TZQtO\njCYYnXbLNYs9X4rkVbmCRSITnKmz1OgoojTW1axRqw5NPjWWYngyRV6bxVazzObnEHV6t0WKhtCO\no5OsSQT08CSlGPYiyzFWJqldts9PKmMxPJUAIZhL5QO+J4mUoGoLT71SjzNeuZeQskLheRtbP74Y\nmaVYSMXC1tyPpzjBCIJXY9FsQcpyyw594uMkHq10idw2cCcPDT3OZ577CvcMPlRyGwWlRhUNrBX3\nyhzGO3Yz3rGbsY7HmIq7Pmy/H12oBe86gq2UwJhgCfbUJNO33VKhIJ85MsnwZLomVa1AMjSRahhl\nU+w2F4sIHPL6FAV9FuFNna93tGZbCFV1G4Y6EUTVdc/ceTsjN32qvN+TuW0uyzMf/yiH7qt0x8ym\n8uQLDtW33MaVrWCLck8qQFDVq9/2GqqKt24ebmpHCKbmsvz40RMcOjmLecLvDigr5uK5sgWnSn26\nZezZ2UB3X/U7e3homrv2HWg5QkNK101RHdLpK1H6q6DNYaktNHJ+mYTAEQKhFJCKg61mmM0nmM7U\nhvVajih5dIpjB63cYyEk2bxdk0/fnmdmze7RRI1l06wxm07m+eHDR5Gi0lCy1IxPV0lUNVTugUzP\n5RidSJHXZijoC11hvv4DOu/o4/SPHwtU7mrVC5J88onS31OPPoay71DF/oIoMJ3MMzZdGx/7/f13\n8r3dweGAidgAw10Pln47ap687i5aHBjeWMexG1jW3+XP5hifzfLd+4+SzrmKzs7bRHzurtGpNDff\nd5SH9tZO7Cid01PKxcbMUVvrEnclxrly7210pabczyZgSb65Rx9h5AufRfhcCv6ViqDcuHTMZMhb\nOfK2Z3kqxYFCKv4tYpMjkU8xNJEK7LUUUT0to5ZOUD5TrmBXuiGq8NvSYzNZEhmLkak5tgw+R2R8\nOrhgaWzIbSTt0uQ3d/vYV77I9O0/qanL/2wdIRhJj3HH4B2MJUdrygYx3ygZ0cpzDvC5V9fiWOUe\nieUI8pa7AtTwZJrZ/Bz3nHqQVpASbE+pW75vNW85816QfceTJ+gbrF0ovFko8ZahQzx577dx1HLv\nx1Gz7m/FvXZVW/rYljNeuSsoTM1lyWULNSNVQrEavpyt2vi9cyNsG9wbOFtQaeCbG7v7HjYHzGzL\n1lnQYN3xYzx30k2WZE1OMPqlz1MYd/15qWh5xl4sb7Nmttw4KFJ49kOlFZWMnqR3+hRX7P0Jsbxr\nUQX53P3v5tQtP2TPN29hcDxF8a5c9MQJLrrbRCvYzKbyjHoNk3mq9kUvISq9qIoMcA8E3Lo1M2XX\nlayeKuhx8sHbGRg5yNGDDVw2AQ2xf7DdcUSg1eVgM5mbRiBK9zPoCZeUuqzsoTSTvfqEResxrd7D\nuon9nP/sc3UO8RSUdJVeUPx1znOrpbIWP37sBEeH53jiwFhJifldZA/vG2jYANW2WbUXIxSrQmG1\nStHqTj+/j+STjzeuHzyl7r6/lu0wm08sKKeO//uod3iz0857YpeUbB49QvbR3Uil8ruXOBSvdDl8\n7md8KGQp5jrgY7a0JIrUiTmtLMBRz5YrExSJExg3LiSDEymCQp/LL2Xtzg1TaTZMpeFNMHvP3TiJ\nBBP338WDl8cryl1+aIy+RI7HLt9COjJETJ3FUpMVVlMm4lpm20/OoAuFdZMnyMR7gmek+pXN1CR9\nEylYW16js3MuB5qCkyowk7fJWzn6as9SwdDYHCdGEnTE6+fKCbrT/vspoeJrc4TDaGacRCFJruDw\n02cOUOjaRjpn4Q8iS1lpnjl+L3RSMcFL+sJdU1aK4a77S/viOYsNngJBugO+SBXNtkBKtIJNzBeV\nUWzUFa/Bn4+qUXyLs7g+cYkqJLaaRSfe+FifOS+wAI3JuRzdHVGiunttj+wb5fCpWQ6fmiXbZpFP\n5lnfF69QXANDM2yYSrNzU3drsiu1F1nQ6oQEN4kPPzk3yM7Oi5i9+86K0/uxnAIpK01nnZm581qR\nyRczYdmOL/f8/MgVHKwgn3mDOxixBRJR1wUkvf8th8/9jFfuxZCCoPhtd7ft3XqBUKoeTLD7uS5B\nbpkgy/3J3Ud46tAYV46OYyEqZmc0sgaL5AaOldwKY9kJZnKVMet9XlxvW8FhvPMQ0WimQXfYAXRU\nYXPu8d3upioroVqWogKpfmlVz49tqSlm2g4S5+K61/D0wXHWAMlsDltNoxD08ga5kyp3+0scmzvO\nXScf4HLcRjITOcl3n7ufnvy5vFHI0mzTyew0M5lu6KhcdGU6N4uqqGwBxrKVEQ6XmeP0pnKVo6eK\n4PK9PySd3sH5yWNE03mK9rJacqwXo2bq3ooaFCCdsyvGMtwBWndG41wqT3dntEKBBVmqeXUWjXaS\nGTfCY/O6DrLHjlLIVfVJldJfvktz6y4m2GuuCfyNrsBegMVe5N6TD/BY6gBX5hOlpFt+2bJ5G0eX\nWGKaiBpsHPSOzDEuZE0+nGrylqh4jwuWQzTSSJE26OlLyVxqfpa77gik0kjGouW+9Kr4jFfu0svM\npDYYCc/rrSy4XL8FLqgJNBmvWFBXEZKdTxxH2LXHaLd9mwvtBGmv65zNFIi2R1FcUZvGL0ze8sNS\nGTExR/sTM6hbetAcyfqpcjSFKiQ//8gxRIMY2aIlrNuNoiqCrztaKHDOUPneqba7Ko+lpbC0FEnR\nB7iLg1jC5s4T99IntpOZbce289hqFoHtDaDW1h9sfCl1948e28/OPcd91+aQip6kJ3+u63LwWWQ7\nHz9OrruN6W3lPkYxD8hjn/oCJ87bWnHuTq+7LaUs+WgBCvocsVN7axSCWmrUi5Z70FhGfSZm3Xej\n+OjcxkLBEYLpZL4mFE9KycRslryovI9CyQNxLE/m6Vt/RFfnNugqZvqUZb+274YW3XPN1qsN6mcW\ntGSNi2E+KNLN2DiTn6ubUbFgO8Q1PVB5FyyBPpnmgrHmSdMC3Tfz9+iUUKQkmi5w4T0mw5duYnLn\nuoYLx7vvSfMKtaBZhIvkjFfuthC85OlBOtOLW1TZUQpYWgpV1FoKQrUQWPgnaqQnkrSNJrFsh4Lv\nwRRdrZKyVTY1ncFO5dlckX+ikYVQ/ugzsxm2zGZIK9CbyLN+pqzc414CKrWFLmp1wjA/U163vtPv\nQpGSKw4coS0/B94KWYojSn8D2NJiJpmnryvGqeQgJxKD3Deyn/OHz0VTT9GtNl6ApZnU0qeYTiWH\nab/zUVRfDvTeZB5VSGSsHFIpcf3YmqrSlsih52v9yrnhQ7QVxuCi8pRCf/PYzBoE2DKWZPN4kmxb\nW2sXU3lh5T+9v1WfMu+dy5LXlQrvRsEWpLIWjmIT1AnyK7HY9Ch07cJRCkjFF5NRYdA3Vs7FRi5o\nHoj/3V4QUjKdyCGlxBESS83iKMET1oIazVaeT8PqF7gPoC1v033cNXjWPT3I3o4YpyLlRmbb8Byb\nJpLsvmQzjq6672edZEIS4S7VSGi5B+IIsWDF7vjirEshhGp9JfiA+TwF28F2JNlEHsvrVruDc+75\nBse9EEFfQ3z+iWkGtvSiiNpgzSCkT7sLz9SPWoKuqljjaIMBsVje5qKjkxTVViPlnrccJmazFcp9\nzfQp2rNZhOp74ausScsWfOWnB7n+Je2IaLnR2TlwJy0RdCNKIW6SwdlJMh099DkWtx67ncvtHELK\nUkjbuYPu+MHzl1ol0eZSBSxbYCtuvkY1W9mNllJiqxncCfD++eKNn4oQsiJ6ZuOU658fXdfK0c3x\nW3gv2jfMeFXucEc6LdehOA5ZfZzpuDvg3O595v7j1SaThOr5iMUiFHsxkGBwLEWqI0qu4HBiLImj\n1zcCUoU0lmqhi46VWW66yU3eNJkiMpsl63371z94lP27srDebeQvHJgs/btmLsvAOfVHp4o6R0ML\n49yDWEwrPt9jHx58gslZ1+LQq8KokoUUuYIV2A08ZyzB9U+dZGY26/OzNrbcAaZyMzhevHpQsElb\ng/zvxsBUhZWv2wUEDo5S2UBIJLaSQyIplBoAyc4TtStY7Xp2kKv3DfuOFQhs7jh5N0+OPo1qOejz\nyo9Tew+S0aMIHGw1jaNmGRs9wNN3fKd0UyyrdnBKFeX7bpfi613/dcGXd8QRZZdLsWZFSIxjk2hN\nZiQW6oTNxXMN3F11TqkLwbV7h+hJlmVTpQRFlKJgNoynKkztmfw0lppoUcFL0pFylJbtCE6OJ5kr\nZkOVsjwQ3HKrJHGUAgV9dv5pGAPOVa64/rlyBYfpTBJHzS2+t1Bdfx1amZlq+d5xVUp2nqqdobpl\nPEk8b7N1ZK6Jz91FW4Y497PAcl/Kh96YSw+PM7ShC9mxpkaJjaenUdFQ6Kpv3TjuKk8ABb2+v1BK\niSMlyUKq4qWu/qZiAS6HIsVufrGfELHz7ocJaCJK0aJ3o2wsbNIMpxO004PtVLYklu1g2aBrKmvn\nsqhCIFQVEF6sroKTKXDJHQfp66i3blDQddZu04RAqE5JblU6JB55DC7bQsFyAiOWZmPPkLfztMf0\nmhmZUV/YqT/vS7FUXyLL9pHGeUSCZjIXiZeWNJyfwutL5tgxNMuzF7pJzKoH5hVRmSle4vYqVSf4\n/vqrVwDFZ7cVLFe5ON7cg6v2j9I/Ow7EEAicJjnLwQ17FIvws/u5av8oe431rkxK/V53xT1VJEIK\nLG1519ad78QmaDyGFrHdgfKGyOWJcz/jlXt1gqjlZNNkig1TaQbao1hVLhG3NXeIIUpKtBpVSqQU\nFJTGvuisnSOmVD4aRdb61htZ7tVlNcfC8k7p+vpcS8EfQWTZglkrTUQGh58VlVy04CAVgSIsJDZI\nSWJojoLtsGau9WRfQa+87oiaBEwAJLJ1rSop04xnJ0lnZc0CKPVcV8XGT3MWZ4VGG0x0anbm7lQe\nRUquPDBKb4PMhm7MgPdDCSxSKjcxl8XOO1xiJnjmwk4cbzyoLW+x89Qsx7b2sW42gwTyWg4VtaUJ\nZguJZ69HW8HmRc+5PcDiTPBmFNTEEvQYXNxxsaU5V5EtowkKAVE4qmjFERta7oEY8fNoba7d0qBK\nyYVPn6o7u61RF0yRsqliB5jMTxKzKy00NWBSTKyBci/mPnFDdKpk9Cn3iu011mfl7+K0pPaczTXP\nD5PoTHHQ6CaeyhNpEnXRKtXuriJqA+tZEwIhBRmRRlCpJKMFByK13kdFSnTbIbqsxkHjj1q3BfGc\nRf9MvXfCPd4/9d+f66i6jnTOKuWa6Z9O0JvQSXTGuNwcY22x0fUnI1PsJXV2LCtLpNhLLOHpdEdw\nSZ28+1HbaWl1G1ULWvNtkXIt8flWnB7ZyTh6RcKn5aZRD7xRKx0rOK113yVYVSFvmiNqrPFG74zm\nc8sInIrlwiwv7jwiKheELoZpChwUtFo/v1d9n5eoqTs1xZZTD7J9Kr2g7mzQvdDrnKeRcn/xXndW\nq6Pkah5OvfU1NSG5fs9Jr9u8PDQb0tEdQVsd19r8dU/tm6c7gs3jybJih3n1rM5WFvKuNqJR760V\nJKFyD8TJ55nfwm+Lp0lcRd0962abW+0AedshqmkVl6WJWgu8EUUlKRQbR6/8oCUOUnW8iVL+EDfP\nmtNnvZDQ4ArbfZkIt4wnkUsYo1vPcm824AlAnV6T7ciKQTBwr2E5FTs0H7BXqN/7klJiZS0ierN7\nKxGKhSJ1EoU58lrWDb1TBFeYtalw47mVM4JCWkdT9SU3Txes3A3DUIH/BK4A8sAfmKZ5xLf/D4F3\nAjbw96Zp3rpIWQMRuQBf5TLTyPq2tCVYV1VSk4kxyHJvRMQ7XjYYLKtOsuaGYLqvWKOQ0I7qNLNL\n2MWtp3AjC3SfSKhR7MAyu2Nap5FrTQiJ3awBUiQFLYEiNfKF5i6A+bxDISuHdpolDnsj0Gaa5kuB\n9wP/WtxhGMZG4N3Ay4AbgX8yDGNZlvp2cqtgua/C99E/k5mncl8+q7S9SrkvdlKJn3rr2W+aWFij\nuZAEUytJTUNZRauLRsjq1BohZwyW7VAImOm+WBaj3K8DfgpgmuZjwDW+fS8CHjZNM2+a5hxwBLh8\nEXXVReTzK6zaT3+Fsdzoy7Ra+wuR3uTK9zxDTj+ODS99iOdi+gLdgD9A2DEMQzdN0w7YlwQapmbs\n62tH1+cfDnRC93zRK63hQ0KWgGaWe8gLA0VV6e/val5wHixGuScAvzSqp9iD9nUBDZJ/w0zdcLDG\nJKeTnI2aXVGURfcQHFVFEwJNtFWsKNUSUoOwq19iKZ5HPWxNDYwSarlOqSx9qGDIiqLpKhMTC7Pe\n6zUKi3HLPAy8DsAwjJcA/lUGngCuNwyjzTCMHuAiYN8i6qqLzK1saJe+BJEhqmg+/BBrmJa0NRwv\nS6IS8Jh1pwNkQPy3ooBUamZ6riZBk0Pmg7IMK8svBRKFREeMY+f0Bu5vPe14+TnG1LbFCxay4qj6\n6TVD9fvADYZhPIJrOr/NMIy/BI6YpvkjwzA+ATyI++Z90DTNZXEuyhUOhVwKRdGK4lxSfRSQmMZV\n+JXb1dISdCqKVALz2RzcuY6JvnbWT6cxvOx4s11tbMhZDZelWwyp9iid6cKCI1xUBRY5ETVorYpF\nIVF46OqtFCJa4GDxTHcb61IFNFUpDVirIhqYt19BQRExhJqnXe2m4NgNU/Km45HQHXSaoZ1OKzGZ\npimAP6rafNC3/7PAZxd6/lbJ7TCYmTpG90z99TyXkkbWVMxe48aVK9mGoYStNkaqogTmUpkvQY2J\ngoIqtVL6gYiuoWsKecvxygfLaGsq2XgEyzc+cvDcdWw6uHzzhIWi4GgKzQKBVRmpmKxVJlg1F3Rt\n1UIihQrZNjcLp63V3mtLd+c5RHUVIYrPpb4CiIgOdKUTTXHLJNujHN/SS7IjygXHp1k3m0EoCic2\n9zDT3cZVB0ZBquiyzbcea8hqoS1gvLEZZ3xWyELfBgY3b16x+kRMZ6YruOuroKDJCEpAm7lv1/qK\ncs3oiLTTGWsvtehznTHufdGO+QlbqibgMUuFiOh03TO4izO1aTEUFHQRr5Gx2GNxPEU02RenoGsc\nu2AD6zcufCCopickFTQRr95U1zUz2eum7dVFO+30Brqa9ADlCXB0a7PFAv2Ctl60FfxpwZwAq83f\nayrfomAhFM+NpioaKAqq1JnpiTOyvotUR4ykl8xtaEMXh3esJRdz38+I6EAXjZf1O60I6kquMG1R\nnXis9vsOzF49j5dGXYbFOs545W4LgViGRPf12H/jRWSu2dpk5mDtQ81HXeUU0bVABVRNf3wtffEu\nohGV6Z44j19xDlaAgmvFH61IpbQIiSJ1T0LNVeSyrSRxmx6jW+lHk+WskdVXJLyuSyGqc9+Ld6Dv\nfBkXbr0cJ6ozW6fRa5WxdZ2AWtOwSBT2GhsYDhg4GlvnNk66iNeslmTrGvGYjqoqxKKae++BVDzK\n/dds59Sm7lLj0Iygz9Rq8EFGm1hifj3lBJxHKP67UBw7qacsvP2K+5cu2onZ62iz1wIwcE4v5o61\nHNm2xq3Pa0wUlHmNIaki2tK72wpPXbSRXHR+3220pbWQl5d67tLBjbUrSuVi5XdAkY3fh9ByD8Bx\nJHKp/FWtWAaKQmZNB4PnruPE5sqXTS19NLUUFbPr8GitRW+lXL6lwUbXSo/aPUSdHuJiXcC53elD\n9cYUipuLg7Rxq59NyevYqO9ka+9W9t9wIU9ctpmDO9dxePuaFmQq1lrmyI61DGxdR6qj8kPRIyqi\nu42Jl+yoUUb+JQZ7OqJEI2qpt+Nv+FRFKVnwUoF8TAdF4alLNjGyrnKt1Wr2n7+eg15qXj9BjW3p\nupo8Ov/C3UFuGTWileQtFQ1SrFJB8xroHs9CV1CIif6SQrF1jRNbekvyCu+8nfEo63pbt9x10Y7a\nREm1ylxXGwd3uo1PxKlVjNGIRluV8g9eh3d1kcDuSzZzaMdaslUWfT5S/q3Kxqmwl2OZvbNAuQvk\nklnu9b/ICqtBUTh1Xj9zne5HpSoKsYjGtg2d9Ha1BTYStvfwNE2hM17/QWuqUrJAWxm8DerSu9sV\nQEUVUc9KV0GJlWxAP0XXTEekvhVblEWUGjANFd21FFUdqSqgKJzc3MP4mjor1gee2CezpjCwtR+p\nrkETcXSng554BzvXbWZbfw/tMb2mx+SoCgXP6tE0hXg0UlKGdr0Ppuq+1ksuVmR4YzfjAa6nYr2B\nr02TRyd8gzfVlruqKHR1t1U8/7aoRmdb7XsTc9agySjbNnRVrKSV7OqvaMA1X3229wz7utqIRxs1\nUNW9txaNEln/eyy+20JVSg1c0Hk1VSk9pojTRcxesySeMV1XiceCXSsLQSoK071xHE1lz8Wb2H3J\nptK+fExDE3FP9sbSh26ZAGwhkcrSPKhGA1Zq1QurKCC85xWLaqhq+fFpss3zG5cfqKWrpQ+sr7O+\n+6ItEmVz5/q6+6uZ6Qk+l1AUdKeDqOgqu1Tq5K/QZRvndG4h6ltpXpFahY9fVRU0VUWPVSkDBWJa\n5bqzovUYvoqX3v3YXf9xRLSjyzY2tq/nvN6dvGrrdcHXqSoc334VqY61aKpKf3wdEcW9J/lqWYGI\nrtb44IsDm40FrX03ij0DNXDAunVKDb8oP0tZrVgVJcDV43vnivdcVdl/0atIdK+vkEKtaEzcvzWl\nsbvRevUAACAASURBVCUcdFWySTy97nQQdeqPwRTlFKrCxnUd6KK9aRiSImtddacLsahWClvOtEeZ\n9rn55jrbyMTbSXatb+oV0MJl9mpxHAFqCx9nCygNHsBszyaeuqjcNVcVJVCJ6Z6Sj4j2isZiw+Zu\njv78hWR746gBiqLI+rYNxPWiH7yqW+7jwM513H/NdhKdwTHzyY7y9ky8h0TXega3XFy3XrWqEk22\n0Wlf6vPRQzSiEiud1ysvoTvqfsxXbTuPyzedx8s3vYaYvYaY1oIP3ldt8fb79YeiAqpSI1+R3vxl\nXH7Va9j8m29GVSCi6qyPu939uXPXMWZsYNrnJopHYnS2VfYsjm7rY2BLcKx5WajaXZaXJz64h9X4\nYxZBylaWn1lQb6KZMgaIx6Nk48VeZrkOv1Ufc9YStXtKkTV1Za3ZrKCLxs9Ul20NjSRwxyM2rO3g\ntee9xhvQDa4/okZQpF7hjikOtmuaWvedWG5OXXEOJze699hqj9aIX+y5znXFeOqyKxnacknTcy7F\n/Jmacy75GVeYreu7GMrWf+E00eau9dnCajONPshjO69hsufB0rTbjjYdOx6hrapb2xGPkFuzgdTA\n8dI2XVOJ6BpWp4aja6hOgx5CLEZxZfqYFqU31sMwtaFqUlXIx3RESkGRekVc84nNPRw7p49X7HYz\nQKTb+zi5/Uo6k5P1r9z7UNb2tJHatJNj6hra7Q0oUnX1W9HVoatgi5ICFlLSprfx9kvfiq5oaKqG\nk80w9Gg3U2mFvF1AQa0bd+2/41JRUIRSs19RFLZ2ncPmzo3Ac+iaWsrJLdQIOzd1saW/kyHvmPY2\nnba8Trwrxtj2NawdmCqdb1PHBqzOtazL7CQTGSYTGUOoKod3rGXnkLcMoaqiqqDkussNbIDsJctd\nLUdGFFerau5zL/9dch/59Hk+YLlCXdXRRTuOkq+bKKwzHuE3b7iAB58dZiYhiUU0+nvjqKrCjLeg\nii7aUFv49BUvhFQVUVQZRcFtgFQ7Sl6fbnp8PTRNIR7T0Zq4U7uinRSSlTN3dRFHE21osSQDO9eS\nyFpccGLhsgThf7+CmNvUjdXfwexeldnLNhPJatjCKc0Cf35XPwO5Xua62ujOqwildk4JUiUi2ktZ\nZDVNYalXDD3jLfcrz1/HW1/9EqCyW1skIjqIiE5idmXYm66pNYMYjSwOWWVtK4pCb0+8pBSL1uvm\nP3wHV7z9rbTHXEspGtFKfmKj7zx29mzzWUy1dP7m79H9s2UXRG+sG1XWWuelNVIVhajTTcwuW6fm\nznXu4FnJ6PQWjW4w8FxURrqqcN3v/ArJvk2V+72TOVWugaIPNaZFS0uFKbqOpirE1DZiTp8XfdMc\nTy3WyqbrRFSdXz7vF9AU934WfaZCjQQORimK2wBC+V93u4KmqcScnrqDXO69ULw1cevfs/KArTvm\n0jz3epmKMDlF4Y6fPZeT264qaf3JnWs5deU5Vce4yq3Z4Nx63yCporiuKE1V6IxHSoOurVB05UTV\nGLq/V4FCxOlyo2cWyJbOTcSjRTnrt4Qb13ZUDPoqKKjeM5na2M3IEuZj0byoqnpWtKWp7HvtxYiI\nhhaPMvHiHVjtUbpZT0SUe4NWRGOuFDmm1OiOIJajF3LGK3eA9Z1ridlrXP9dAF4UcM32SFXXrmG4\nUsDNL3atd3RvZU2b263X2jtQdJ3+vjgdbREGrt/FwVddAMA5XZtZE28cW63qGp1XXc26X/0N4rvO\nByAZ4HopWntCLV5frXyW7jYwjucTFw1esoqjfS/30BW7UDtiHLzB4PkbL/YpSoXzt/Zy3WWVjQCA\n4vPtK7iNriqiDQfawG2o3GUKJZ3xCFvXux+uvmZtqYxeZe05eldN76l0Pq8x8/uv3QHgpfmQigOh\n9az7qK7VnXkoFdi4pt2N7tHcwWgFjTZnjeu2UxRmquPwazw1ta6b6CZ3zocQElVWuiv7e+N0tUcA\nhUy8HCBQLwJGVSEe0ytcOkU0GSUiGkcZ1Rzje6/ecN5r0fQI6/va6w5uSiTxqEZHrLL+3qLi1IJn\nUTeike++matHqgoiIELKnUAcfJwivR5pHWmKqEv0Tvo5490ygDeYWS8TeJnqBFqK4g6IWNkISM31\neXpdo4qFe70QtP701bxy63ruO/UwAKKBpbbmNTfQkZ/icNsYBcs9VyuDQrquoagqsc2biazpI7Jh\nA9MjU4AJwBOXbWHLWIKRfvfDEg1exoO7LmTXqQQjGy90L6MFCwIqlXN22yZMXyp+6Usx8LqXbA8+\nvqhUS2s6K0RFF5aaxmkwLV4qoEoVcNA1lVhvD51XX0PHZeVs0ee96bc4+dSDGG94K5OjU2yL9tJb\nZ9yh5NdWYEN7f6lhiGgKv/5zu3h0eJbHhk7VygFoLdg9uairdGJqDJvaNWQ1zY34COrhC8V1TWyJ\ndTI0mcZxHGZ7N7JpJM7Jy2pDA8F1N8UyGo5QAtc+7X31DcTP2wW4inxwcjsbtvSits0xk3NdTsWe\n5oELX8krX7GRiW99g4jTjaMUSouL65pr6RcV3VKk3IhFtFoFpih0tOnoWpzkdG1qhWIP11/9zk3u\nvZlLuCGe1QPPfqIRDU1VKFhOy3nxq+trha54hNm6yVUUXn/duRw/WPs+qTKKJmKoMkZEV2nFcTwf\nzgrLXStZUI3RRQdRu3YihIqOLt0wQXdAqNw6R5xuYl4Y5Obu9ezo3lbaZzWIsui45FKMG1/Pb1/8\n66VtjhRNpfR/AGpbnK6rr6WLrWxKXkfc2sBsd5znz1+PVBXWZC+mN19/sCbf1sHxHVfjeBZ8y8pd\nVUu+4+oPMqqXw+gaseF33458+c+3VF+5YoWo00vRItXa2+m8/IoK5dJnXMIVv/lHtHV0cc55O7hg\na52BUKhY/i+qRYkUrX5FYdPaDtqjVc9PKqgiSp+2njXR/ubyRi/nxI4byF5wQfECWrlKr6qK0QYA\ntm7tZ+s73gH/v70zj5KsKhP87y2xbxm5Z+VSmbXdKqiNqqKoglqgClmFYhVa1AFkUAfbVmdGuz3d\nY/c53acdp12QbnXswbbdxm6XPiOescFRh0EUcUFBGq8UIFBQUFlbVu6Zscwf70VkLO/FlhmRmVH3\nd06dynjvvne/uO/G9+797vd9d0PxbAgss8GK9hBRe0HYk85fGA6duxHdbz2XizZ1c+C8lVy/cR9R\nr8MIW9PQzMxiuZ5vdtG0vOfuPu6s/Pvm3i/zktX0OZdfbyqCkZNQr8UXJeQJZUTN1pjh+Kp2AhEf\noWB5Zwqvx8h5UbmXq+UVFvWGuXbzBaxa4fxC1tDp6YjQGvUVzQosx4swRtqTDbBbSJpCuXsqXGnW\noKKFpFysdAI6b37DOm7avzrP0yXlMXh272ril11R+Q3tB5yJGC2qz2l6ltbQMYlPrWfF6N7s4UCi\nEzM916m8yWieHbTQzFQu2Mvb3UNs/yWANUoEiuzIAZ9JVzzAeWtLu2uasRirN6ykJeKnM15sLsv4\n1uf29/aZjcSmV815iswjOK0j0Mb6rg3Zz7k/rNjefQCsbzmH4GxX9vjLvUOY6RiRoLdIceU+llc6\nIwzHg6R0L2PRAVLBEoFADo9T17TsSxIgaJsl2lv8rO1rcTQNZDyowPIi8SVaMdNWvR2tIUKbt+SV\n95gGW9a0F5k88m6dVa7u4pfDkwznKeVy+A0fXUG77+jFI3OAhMdyJMg93NsRZqDLekkFz9nIq+f2\noKHR1hJ0NaXkHs3Y0qtZF6mE2zbcTFekle5WtxgRDd008ZoGvhIxBW4pMuZD05hl2u98B0efexke\n/VL2eDWdLhcnl8gOe1FntmB6N9kSxIiUXtQZiPTy0ugrdAU7stNpTyoKqXSR14HTFDidXWq03FZi\nU6uzi2rpHPc4Pe3Bm/YQn9zAqO/FbPh5Biebe8jvIeAzCW3cRGz/JWi2v+0N+1bz9O9PMh49zu/P\n5F8T9HvwVOCX6/GYxMNeZmYtu4SR8pHUp/AkoxhpD0kt3wsolOpihsSccp+H1gl5gly08iKCx2OM\nnngSjWEAet/zvmwZn+khPrWBKfMkKW2WI/193HbXdQx/5j5rP1IsF9hoQCca1hmOB+k4NcEzq9tJ\n6TptE1Z76hW4KObi8xocX92e/RwN+TANnZ0buhzLdwU7CZj5C5qZvjDUE6HztrfiaWt3vLYQQ9cR\n/a3sH1iDZie307TSW0daytO5gOW+qZN0MEs50RFsm3Pp1PPXLIy0D/QZWtpW0H3H3Uy98AKnv/89\ngLyXIbpGyBNkfHaiKpu7pdjdv0s5arlKS1szpHKznHqkpW4K5Q6wfm03/sQUhy1zuO09UmmDFU6X\nTIxUwNHLwylgxQjZ+U1cfmCXrbyE8cQELb4YGWdEty7mNHL3ewwmc3atD8/2Z/+e9RS/wIKJLoKJ\nYkXhZJaJhb0EW2K0HLg073hbzM++LSt48Pe/LboGoMVXPs9HxvaeaTIdE1+iDQ3LC+L1qRFHl7MZ\nbxBmRrPtWiuarrOtczNj7WlG+EHR+cyILzK9khH/YYKJTrw5IeO/2nw1Kd3gjy4Z4qmXD/OtDWfQ\n0+lslG7mi2mG8wh0rsQcKU3jtwcEMznmBEPXiAS9rl4ahfcNBzyMTc7SY+fVcQqwKsVgd5SethDJ\nUWtziHKJRytWPBVp2hxzT86aCFiDk8HWAfytnZZjgsd5dqsBf7D+Rp47/QL/98VHytYY8gTRNZ3R\nmTEMTSdFbdtElg7Oczun2QOmwvPW5+620ILPJjI0jXIHmMlL2l25RdCp2T05njdnInMmCKcAJLMl\nTvtNb8KMONvdPIaHFsNShvk/lGIJnVbNr949yE+feZ1nXy7ezCppejm8ehe+qTH6Xym9H4qTctfQ\nqjI2dgbb2da5hcFof/nCDtPuzJ9zprTiyl/q30w/rxDbu79ywXJlvO1tmLG5l8/cSya/rkw65dBs\nL8HZbrzG3Ms8nSa7VjEY7yeUaOFbv340bwF7Lsisuh/njIM7Ym/Y2c7uhGlo9HWE8PpMZqYTc9+v\nQrJ92L4uHPAwOjG3nFf0eyij3PW0J+sLX50gxWtlRo5PuGu9moZHNwmY/oreJx12UFvYE2KWGY6P\nn3K5b+n7lFq8dceelbS1MuEbw3h9NC+Nt6lr+FrqkxCtqZR7b3eUE1qcmUQy7zl1t4aYmknwnLeL\ntpMvOVzp/tCe3Hg5KT0nu1vBA+6LWK5nvhW9lQnp0kFe6o7xenuIgw7KvS3m56pdK7nXQbkDjMS6\nCevuAUoZUobJkd6NGF6Tnhd+ZcsDvgFnrxcnDM1gKDZQviBkTTzVho6nDJPpc3ZihKtztctghELZ\nxUKA4PoNzLz6CqEtW/PrSc2Zu3LTNOuBIEbK+tzfVcrkZq+f6JWbZZyU0d7eXfSEnE0yGflK4TbC\ndSMz+8zMONqifqJBL8+dPuFYvtzT0wBvqjJ/c++KFbTuO2BdZ79kDF2jJeyby+qZqdBVmeaOFipf\nIfUZXmaT7j4p5b7nbA0j7Myz8954DYef+1c2P/AU6XSaqWl7YHHwMlp6i5PSLQRNpdx9Xg8D7S28\ncnycmdxdgTSgs4fft2ydU+4V6ptZr/ti2dvOuaWikHA3ckUYjfaieVfXbHsr7whq8XrXGsLpKTLj\nxODBK2g5V5S47zxsgQXT7mMdq5gIxhh88Ymy7e+4sFyG9ptuITk2mvUYyaCZpuOid+FiY2ZE1XX7\nnXQBvDrm6gUBOWszBYth+b7t5b/HxvYNZcu44e3qRg9WlrY4YPoZiq1kS8dGW7S5mZXXTqXw8I6V\n7HrxBC1n5nz7avPBdjY8Ri7ag7erK3Pj7PF4JNe8mOk3biN36z9PmbQjGpbXTS4eO+bD1A3cdn+J\n+1pIjieANDOmFeX9WluIY+f0UE32e13TGLRTAWfiYMAaIAY8PvS0Tsu559TFUwaaTLm7TU+9l72R\ngQ1reP6nLxMJepmaATOnbKECCwe9zMwkaW/x81pHmA2DzoFHpbIoVsv66Ca6znFXsuXQUpXbEXPN\nM77Va/JGuQtJxl/ejET5t/gOJgNR9FSCwRefKKvyaonY81W5aUtr1M+hvUMcPjLC0y+czNqedXsk\nvH5luc08LBnTOZathcg2uCLczbOnnp+rxS2vzubNeHZXbroKe0Ls77tw7r4Fi+KTPpNpn8nTOwZo\nMQ3OfegZADyGQU+bl6mZJKdGq98tM1f+XBNWYf05hfL/dznfHepkd88OTvEkOHj+9wRX4PfkP4+I\nN0Qy2I6uGYxPv5qdvdk3BiDmi3CSfC+C0UvWVaXYAVa0h9i91hpGBcwA79j87xib/TnDRw4TC8ZJ\nDh+vm2KHJlPumYeeZ8PTddrbong9JtfuGWI8fg2nv/sltCn3bfC8pk6HnW3xpotXF53f17cbn1Gb\nJ06GeMSf90PZMNTGwNrKPB6c0NOVJ6bIi9isY/IlTdfpvusdzOoGkw9kFmbn6usN93ByfIyTiWIb\naKM2tR7sjnL0hOW1ky6zstje4ufEyFTOAmT+zKQyyhc+v+s8ot4Iv3j91/YV82uLjW0bePHMEbZ1\n5btLaqZJ61VvxIjFmHruMM+PGpBME/B7SOoaZ7qjBE5bG9D7vQazJfKtuOH3GvnKPXdQVWZQ4d4H\nbHOYprO1cxMPY5B0UO6OC9QaBM0AM6lZfB6DVCq9IHv/Okqq5a/R6ZpOdMdOojt2zru+SmgKP/cs\n9q/OY9vuIkEvg0NdBLrmFkRD527kxe2Fi4HV/XjObVvPmpah2mS0O2xL2Mtgz9yUUZ+HTzfAlM+y\nT5+JVBB8k0PZGfc8dawRDOL15ixU5uTw9ugmhku6ZqMOfr9uJBKW0vKXGXVHAt7sNBsgk9Ki1IJm\noX6qxHgW80XZ2b0tp57S5olyDET7uHvT21gVK15bCaxZi7ejk+iuC/F2RhjqiVpKUdP4/fkrObam\nY07J1uALWJQTPlfRGwbhbTusZHm5ZbJ/uOXjL/hY0IlNQ8fncU/9YN0is16SO9BxLV4W532KnR0w\nGkVTKXfNZymRtoif1qifzsFeeu66u2iEMFDg6ZE7YkujkRpYVX9hye+j+jynZ1OBKE9vOMAL6y7k\nnYc2sm9rZSaKRoyQdV3j0N4hLtnWSyWj3aGeKOe6mMLqwXbRSV9nmBv2VffcM7lbQk4RoCVYHRtk\nT+8FgJUWoRxujyhdRUi9UcWib1H9GfNTldc5JXQrjAmI7dlLZOcFBRVmfCOdv3ihIg0UJPvKRNiW\ndlycO+vzGmW3RSyH0+9I05xzPjWKmswyQogY8GUgCniB90spf1JQ5lPARcCofeiQlHJkHrKWRfd4\n6Xzr7Zz+3oPorx3FKAwvt9netZXh0G+ZSkwxOjvOjB3JOWv6eGrjZew7rw+//An+VcUmmXpRrTub\nE1OBKEGfB5/XYOuadjatauPvvvVUUbmk6SNheDnR1t+wnNiD3VFGxqYd3MnyVUZXa5Br99Q4K6qR\noN/kxv2VP+vAbCeQyir3tkAnwUArYzPjTCXLBPNocNngJQCsjg2VHNllFv/cMlPW+8Uc9AQIeAKY\n2Zwvlav3cMBD0mEdyLmfuyjxMguqueU8Zuk0vYXkm0s0Cnfwa4v6mZ5NctTv5+WeWFl7u67p+LxG\nNvjNQcyGU6vN/f3A96WUnxRCCOB/AtsKymwDLpdSlvfRW0A88Tie9nZmXjvqGrXn8/jwGV58hpeY\nL8qxxCTjk7PW+r5ugKbTds2husiXnilIjpQKoKEtSFa47rYgB7dZaWI1TXMNaU7rOr/ecpVdrvQ9\nL+jezkxylpHpEc7MjM1Lvrwpuf2/V/dZ+blrjCZeDKLTg5jpucV0XdcIe0JMJqac1vXyyFWPQU9p\nlXHb+ht5LfSq+wu4ztpjd88OepMTnH7u+9aBinW75i6bY6RXobYuUbYi0pRrHF3TCJoBdF1nbGa8\n6PyKi3bBeTv5399/mEnzGIEyDzaZTtLTGiSRTHFkeDwrfqPWjpyoVbl/ArLxxiaQt4QuhNCBtcDn\nhBBdwP1Sys+XumE8HsScx9SoIyevc+uhKznV301823kY/uIEV1PJcUZy7Ku9HRGmZhPoPj+J1e3s\n3dFftDnvQsgFMN0WIz18NPvZizWlj8fDRWUL8ZaxCb/7lsL3K/h8nmz6Aqd7dXZGSn7XDiKs6buR\nL/7qm0yNThEJB8rK6YY3MI3X77GyXvpM0MAzm8RLJGsgDAS8Nd+/nnR0RLhz580cGzvBd17Mf8m1\nxENM+kzMWaeNWPLbXtO0Kr5fBP8bDnL80R+7nK/mXuUp7F+t8TAtUyYT9nFzJlnRDHNux7/ism3t\nYXxt+TIbLcG8zaUzfWB8IswZhz4fifjzvrdhaHY2UQvLLKO7/l4yx/t83SSSCSbsRePc89F4iFBP\nnLjeTyy1Aq/v1473ysjhP2bim/TgA/QTE2jorIh3cE7/IKbL9pZu91ooytYqhHg78L6Cw3dIKX8m\nhOjGMs+8t+B8CLgP+DjWhOeHQoifSymfdKvn1Kni3YYqpaMjwvDwaP7BtRs5OToLo8VeMbOnJpiZ\nzvdxNbA65aXbehkdmWS06KqFkcvcvhuv5mXsV78EIG1PXScnZ4q/QwGFMhfidP3MTKLICyQT2Qhw\n8sR4ReHPY+OTzEwnmJ5MlJXT9R6Ts8xMJ0inUszMWPUnZlPZNoDK2qHRZJ6jjzD9njAz0/k/9NHR\nKVLTCZKJFKkyLqlp0lV9P23jdtrP3car932y6JwRDCxoW71hxSU8/vovGZ6wgpnOjEzR1tmPZ+0G\nxn/zFKlk/rPKoOs6qVQKn8dgejZJ0g4Jc2qLkycnMAs2+Rg7M5XftydnGR4eZfr0pGOfHx2bRs/5\n3slkOq+udNqq2+na3L4PkEgli+ScmU4wOjbNzKlxq7+SRHf57WXaX4QETx89DFjpQgKTA1y38hpO\nnZx0vK4QRx1WIW4vhbLKXUp5P3B/4XEhxCbga8B/klI+XHB6ArhXSjlhl/0BsAVwVe4NxXWFqraE\nQtVghMPE9u3PKndD10mmUvh9te8DGwv72LSqzfFcuaRQlc4aMwEjfrOCfVFdcLM8jUS77A2dlydO\n+506YRo6Rg0zQqepfWjzFtovutAawCwQA9E+BqJ9fObX/2DVa+dFaTlwKZPPPUeICSanE0zPJplN\nzClEv9egKx5mZHyG6dlk6QA0R6uMi829QlNlplTmt1TNdqTu3pa5Zs3yN+wKdfLOzbfz2Se/QFdr\nkPO7K0jPUWdqXVA9B/g6cIuU0mm+sg74mhBiG1bL7AH+sWYpF5p5eA4sNH0dYVKk0eexQe7tV653\nPZcq41FRqa3/kv49/Oz1J9jVvaMq2fIprivgNzncuxuwVuaXIzrpkhZZv9fMKpHkAu2403LxAcvk\nuIDKvZAiN0as7KjHR6aYTcygadbWfZno0mjQy2wiRTTk5fVpF98JpwXkojX26rKCdq3dxLHDv8Gy\nDlf7O3KpQ9cxdJ3dG7tpjwV4cPiJoiKFu4Lltle5mIlGUKth+a8BP3CvtZ7KiJTykBDi/cBhKeW3\nhRBfAR4DZoEvSimfXhCJFwDdJReHr7+ynCkLia5buT60RXjhmIZTjktnYr4olw7UlsgrQ6bvj4Va\nyYR+m7rGe27azAOP/p5XTk7kJVVaLhiaRikV65Q4bTng5sY3l25foz02N5PTNOY+uwWyVtIA2T7g\nXNjblZ+LpfeGW+k6fYrHP/1XFdzcnZAnSMR2azVbLFfcbBrm4fyy61vXsskhbURmpuy0ztVoalLu\nUkpHVxIp5cdz/v4o8NEa5aormq/YM6P1qjfiH2ysC14urqHY88TjMZh1iMC7avdKuluDDV3Nz0xz\n5bq9HDzQy7Gvfhmw/YEzYiz+b6JqfF7N0mUVKa46C1Mvcr7b3P4C7vg9Psani+3Nlfh9Z5vIYZbT\nfuPNeAuS9Gm6nrc1ZGewHZ9R2TwwV55M9sj4FVcRWLvO7RLAmsk6308nTWpJjNybKoipUjTTJLh+\nA2Z8LlAmsGZt3XKsVESdlPtNF69mo4M9PuT3EAk21hCSDTTRNCjwICgzWFuSnL+hkysuGMCo8AUZ\n97eUzP5Yivbrb6L1yqsBMFxSSy80SZeUFjE7ZXFbzH39pTvcSXugtfiEY1sVhvGm7KLFZX29fc4D\nkpxjpm46JvSLnL+T+LZij7JcdH+A4DpRewI/LRPwtfjKvblyy1SIpmnEL7uCsSd+ycgjhWvBi0Ml\nI/fCIIlK6GwJcHB7H795Pj+d62K43+bnGMkXIGOOaVRQ1UKwoj3EYHeU2ZP2D7nM7znmjaCZtS2c\n+/qtBbr2UAhPq4PSXEDetO4Qz5z8Xd5+wXmyeIzsRtVuGLpO2BPi+KS101jUG7b2RK3Ezz3TjtUE\n9uWZvpz7UHT3RfDbAp+OCrtbW6CV8dlxphJlgtSWwIg9w1k5cs+wFKZOGSpR7re9YR3XXLQwpqPF\nCq7Ytq6D3Ru7XdcYlpFuz76IPK2tdL71diZX1jYqrwbfil50f7X5CaujLdDKnt5dC5oXJegJWqaS\nCpT7XH76yjtDrkIvZfpJJ/NdGitND3Dz2mu5Zd11Zcsl7VnHYuaUyXBWjtyXJBUo90jQm2dKObR3\niNZoba6Ji6VE926xct4kJ/LjGga6Ihw9NVl2RLiUyPU08sTj6IZZLkBV4ZKDJRdvp/WSrNQVsvC+\npfp2OlnbE9K0SndMsCj0pFkMFl+CRcTNa6aRxPZdjH9oVU0j6fZYgHCgtu+wmGHRUJxjZOvadjat\n68SoIi/9YlPYhivDvRz1HGF8tkRA3hKaLVbFPPvL3JaEpe8du/gAwQ2WF4oRjuAfHGL6lSOkZ6tx\n+XSX1VOwmb2Glbwtq4xLfM2gGWAwOsBAtM+1zBWDB/jxq4+zPr6mCnnrw1mt3M02a6HR01n/6bQb\nut+ft99nNdSyW1GGRbd+FPj165pGV0d4yUWnlqKw+T26SUegraRyr3ZLvKajjLkivHku57xmmatu\n6QAADe9JREFUmrRdex2jj/+UM4+5pWCw0d3NMv6hVUR2nA9AfPs2Rs5MkRwZyQYSBnIC80q5JGua\nxpVDB0uKMRRbyZBDauXF4KxW7r4VvbRdez3e7sVT7vPB55lPGtfFZTH8+heaRLJgFJ7ZcNsTdFXw\nLQcvq7dYZykafeEVJNKJokX53CSAmmEQ3rKV0Z8/7nybBcjOulQ4q5U7gH9wcHEFmMd0dz6ZJJ1y\nbTcSzTBou+YQRrQ+O78vCraubw+0EvVGSKVTpNIphidP4Dd89L6nMEXTWYhDn00nFiDKVtMwdQOz\nMHdvtSxQBPFS4KxX7ouFEY6QHBvFCIaqvvaG/auZLJNErGz9DdzpyA3/UGM2RVlobrtsHYePjNDX\nUfjsMsE9Wl4QTdATXPSZ0tLBYUHVdg81QtVtepJ3jyobOD3r/PtZiH0VlgpKuS8SHW+6lekjL+Pt\nc1+ccaO/s/YfQQaziTpxo2mPBWiPFbsj+geHmHz2d+j+AJrHQ3LU2mRZKfbcBVWH/EJr15E4M0JQ\nOOdIqsxlubpWdlugrVek+GKglPsiYYTDBNcX56aoFzdfsoannj/Bb1+0NqOez2KswpnA+g14V6yw\nTE3JJK9++r7FFmnBcBvpVkyJDTg0wyC6c5d73dNW4FDJxegqh+6+gZXZBdUM3t4+WvZfXNV9ljJq\n+HaWsKI9xOU7B+hqtXYQqiSHu6I6NE3DjLVYo9PlFI1VAeGtWxfmRjW0i9lqpQkJrC7hXljlff2D\ng3S//W4iO3Zmr++48WY87dVtML+UUSP3s4w3HVhDPB5i5HTtm6MoKqDJlHtk5y7CW8/j6Oc+O78b\n1dAuwXM2YoTCePtK5EivobmNUIh0ygpqqtUdeSmjlPtZhq5peOfhQqmokCZT7pquo9U57UGpussv\nvtfW3pEdO0mOjhK98KKarl/KKOWuUCjqRkegjfHEBF57J696RUbXel/d789m22w2lHJXKOrAYqd3\nWCqEPEFCnuBii3FWolbVFArF8ke59hahWkShqBM9d7+TtutuWGwxzg7UTKkIpdwVijqh+wNNFRSz\nlFFmsGKUclco6kit+cMVivlS04KqEEIDjgDP2od+IqX8k4IyHwauxtrm/r1SSpc0bApFE6OUu2KR\nqNVbZjXwSynlNU4nhRDbgP3ABUA/8E3g/BrrUiiWLZrPyhV+1udxVzScWpX7dqBXCPFDYBJ4n5RS\n5pzfAzwkpUwDLwkhTCFEh5RyeJ7yKhTLCm9PDy0HDuLrd95sWlE/AmvX4R9cmD2HlyNllbsQ4u1A\nYSLqe4C/llJ+XQixB/gy+SPzKHAi5/MoEANclXs8HsQ0a1986uiIlC+0CCi5qqMp5eqsX/Rjo9tr\n2Ff5eNDrULae8hbKJt52q2O5puxjDpR9UlLK+4H7c48JIYJYtnSklD8SQvQKITR7pA5wBsiVNAKc\nLlXPqVO15zrp6Igsye3ZlFzVoeSqjsWQa6bCfQS8PtOxbD3lLazPqa5mfJZuL4VazTIfxhqZf1QI\nsQV4KUexAzxqn/sboA/QpZTHa6xLoVAscyK7duNpbVtsMc4qalXuHwG+LITIeMPcDiCE+CjwDSnl\n40KIR4CfYLlb3rMAsioUimWKf2gV3o7OutbRdu31pCYnOPW9B+taz3KhJuUupTyF5eZYePwDOX//\nOfDntQqmUCgU1eAfHCQ1NbnYYiwZVBCTQqGoO42LIFWRqhmUclcoFM2DSkOQRSl3hUKxYPj6+p33\nBlZKt+Eo5a5QKBaM9htuIn7ZFQ5nGqTc1Uski1LuCoWi/jRKt6ssnFnUTkwKhaIBNEa7a4ZBZOcF\naKbK5aOUu0KhqD8NNJdEd13YsLqWMsoso1AoFE2IUu4KhaLuqHXOxqOUu0KhaABKuzcapdwVCkX9\nUbq94SjlrlAoKiawdl2NVyrt3miUclcoFBUTv+Iqet717uovVEb3hqNcIRUKRcVomgYqUGhZoEbu\nCoWiOmoZhauBe8NRyl2hUNQdTWn3hqOUu0KhqIqacrMrm3vDUcpdoVAomhCl3BUKxYIT27QJT3v7\nYotxVqOUu0KhWHB6D11D55vfOndAmWUajlLuCoWi/ijd3nBq8nMXQvwxkNlupQXollJ2F5T5NtAG\nzAKTUsor5yOoQqFYvmi6Gkc2mpqUu5TyI8BHAIQQ3wE+6FBsDXCulDJdu3gKhaIpUIFPDWdeEapC\niBuAU1LKBwuOd2GN6B8QQrQAH5FSfqfUveLxIKZZewfo6IjUfG09UXJVh5KrOhZLrmFfvuoI9vUR\nWS9oy5GnoyOSLdfZ1bJktsA7W55lWeUuhHg78L6Cw3dIKX8G/AnwBw6XeYGPAfcCrcCjQojHpZTH\n3Oo5dWqiYqEL6eiIMDw8WvP19ULJVR1KrupYTLlmphP5slx9PSnIypORLVNu+MR4bf7xC0wzPku3\nl0JZ5S6lvB+4v/C4EOIc4LSU8rDDZa8Bn5VSJoBjQognAAG4KneFQtG8LAXFfrYxn1WOS4Hvljj3\nzwBCiDCwEXhmHnUpFAqFogrmY3MXwPfyDgjxUeAbUsrvCiEuF0I8BqSAD0kpj8+jLoVCsQyJ7d1H\ncqJ2k6uidmpW7lLKexyOfSDn7/fWem+FQtEchM/bvtginLUo51OFQqFoQpRyVygUiiZEKXeFQqFo\nQpRyVygUiiZEKXeFQlE1Pe+6h+677l5sMRQlUBtkKxSKqtE9XlIq1eOSRo3cFQpFTWimGhsuZZRy\nVygUNaFSCixt1KtXoVDUTHTXhaBytS9JlHJXKBQ1E9l5wWKLoHBBvXIVCoWiCVHKXaFQKJoQpdwV\nCoWiCVHKXaFQKJoQpdwVCoWiCVHKXaFQKJoQpdwVCoWiCVHKXaFQKJoQLZ1OL7YMCoVCoVhg1Mhd\noVAomhCl3BUKhaIJUcpdoVAomhCl3BUKhaIJUcpdoVAomhCl3BUKhaIJUcpdoVAompBlvVmHEEIH\nPg1sAaaBu6SUhxtYvwf4PDAI+IC/BI4ADwDP2sU+I6X8JyHEh4GrgQTwXinl43WW7QlgxP74AvDf\ngXvt+h+SUv7FYrSfEOJ24Hb7ox/YCrwZ+G/Ay/bxDwOPNEI2IcQFwH+VUl4shFgDfAFIA78B7pFS\nppyenVvZOsm1FbgPSGK1xduklK8LIT4FXASM2pcdAjzAV4EA8Cpwh5RyYqHkcpBtGxX29wa32deA\nbvvUIPCYlPJWIcS3gTZgFpiUUl5ZL7lc9MO/OdVVj/Za7iP36wC/lHI38MfAxxpc/1uAE1LKvcCV\nwN8C24CPSykvtv/9k/0D2A9cANwK/F09hRJC+AFyZLgD+CyWEt0DXGDL1PD2k1J+ISMX8AvgPVht\n9oEceR9uhGxCiA8A/wPrJQPwceBP7eepAYdKPLuisnWU617gD+02+xbwQfv4NuDynHYbAf4L8FVb\nrieAdyyUXC6yVdPfG9ZmUspb7fa6HjgNvM8uugbYY8t6ZZ3lctIPDetjy1257wH+FUBK+Riwo8H1\nfx34s5zPCWA7cLUQ4v8JIe4XQkRsOR+SUqallC8BphCio45ybQGCQoiHhBA/EELsA3xSyueklGng\nQeAgi9h+QogdwLlSys9htdmdQohHhBAfE0KYDZLtOeCGnM/bgYftv78LXIr7s3MqWy+5bpVS/sr+\n2wSm7FnXWuBzQohHhRB32uez7VYHuZxkq6a/N7LNMvwFcJ+U8qgQogtoAR4QQvxICPHGnO9QD7nc\n9END+thyV+5R5kwPAElbMTQEKeWYlHLU7tDfAP4UeBz4z1LKfcDzWCaGQjlHgVgdRZsA/ga4HHgn\n8A/2scL6F7P9PoT1wwP4HvCHwD4gjCVz3WWTUn4Ta3qeQbNffuDeRpnjTmXrIpeU8iiAEOJC4N3A\nJ4AQlqnmLcAVwH8QQmwukHfB+5lDm1XT3xvWZgBCiE6sQcwX7ENerBngdVgvgk/YZeoil4t+aFgf\nW+7K/QwQyfmsSykTjRRACNEP/BD4kpTyq8C/SCl/YZ/+F+A8BzkjWFPFevE74Mv2SOB3WB2n1aH+\nRWk/IUQLsF5K+UP70OellM/bHfl/4dxmjZAt157p1kaZ405l64YQ4hYs09rVUsphrJf1vVLKCSnl\nKPADrBlbrrx1l4vq+ntD2wy4CctElbQ/vwZ8VkqZkFIewzJbiXrK5aAfGtbHlrtyfxS4CkAIsQt4\nqpGV29O8h4APSik/bx9+UAix0/77IJZd+VHgciGELoQYwFJUx+so2p3YNmohxAogCIwLIVYLITSs\nEf0jLF777QP+j12vBjwphOizz+W2WaNle0IIcbH995XMtZHTs3MqWxeEEG/BGrFfLKV83j68DviR\nEMKwF+72AL8kp93qLZdNNf29YW1mcymWOSP38z8DCCHCwEbgmXrJ5aIfGtbHlrW3DNZI4Q1CiB9j\nLTjc0eD6PwTEgT8TQmRsa+8HPimEmMEaKdwtpTwjhHgE+AnWC/WeOst1P/AFIcSPsFba78QaBXwF\nMLDsez8VQvyMxWk/gTWFR0qZFkLcBXxLCDGJ5U3w91ieIY2W7T8Cfy+E8GL96L8hpUy6PLuisvUQ\nSAhhAJ8CXsJqI4CHpZQfFkJ8BXgMyxzxRSnl00KIvwT+UQjx74HjWIvo9eRdwN9W2N8b0mY5ZPsZ\ngJTyu0KIy4UQj2H9Hj4kpTwuhKiXXE764Y+ATzWij6mUvwqFQtGELHezjEKhUCgcUMpdoVAomhCl\n3BUKhaIJUcpdoVAomhCl3BUKhaIJUcpdoVAomhCl3BUKhaIJ+f+EEARL4gpNXwAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5aee68f828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# determine the trial that we wish to plot\n",
    "n_trial = 120\n",
    "# now specify the alpha and beta cutoff frequencies\n",
    "lo_a, lo_b = 7, 16\n",
    "hi_a, hi_b = 13, 24\n",
    "\n",
    "# first step is to filter the data\n",
    "flt_a = gumpy.signal.butter_bandpass(grazb_data, lo=lo_a, hi=hi_a)\n",
    "flt_b = gumpy.signal.butter_bandpass(grazb_data, lo=lo_b, hi=hi_b)\n",
    "\n",
    "# finally we can visualize the data\n",
    "gumpy.plot.EEG_bandwave_visualizer(grazb_data, flt_a, n_trial, lo_a, hi_a)\n",
    "gumpy.plot.EEG_bandwave_visualizer(grazb_data, flt_b, n_trial, lo_a, hi_a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract trials\n",
    "Now we wish to extract the trials from the data. This operation may heavily depend on your dataset, and thus we cannot guarantee that the function works for your specific dataset. However, the used function ``gumpy.utils.extract_trials`` can be used as a guideline how to extract the trials you wish to examine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# retrieve the trials from the filtered data. This requires that the function\n",
    "# knows the number of trials, labels, etc. when only passed a (filtered) data matrix\n",
    "trials = grazb_data.trials\n",
    "labels = grazb_data.labels\n",
    "sampling_freq = grazb_data.sampling_freq\n",
    "data_class_a = gumpy.utils.extract_trials(flt_a, trials=trials, labels=labels, sampling_freq=sampling_freq)\n",
    "\n",
    "# it is also possible to pass an instance of Dataset and filtered data.\n",
    "# gumpy will then infer all necessary details from the dataset\n",
    "data_class_b = gumpy.utils.extract_trials(grazb_data, flt_b)\n",
    "\n",
    "# similar to other functions, this one allows to pass an entire instance of Dataset\n",
    "# to operate on the raw data\n",
    "data_class1 = gumpy.utils.extract_trials(grazb_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize the classes\n",
    "Given the extracted trials from above, we can proceed to visualize the average power of a class. Again, this depends on the specific data and thus you may have to adapt the function accordingly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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166j689kFrlHuOGo3433n/3BsLFrW5I6Lx6NZ7qLhEwja6HLRMo5NGyl9+H7bx7u++7aA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\nRqlxD8+xZrX5KQ/f3/b3brtFWL5c6xElW+6DB1u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r67kiJwDBILHaWkJv7+tlkCbbWXI3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\nLLkbY0wOsuRujDE56P8B7UsPKrpo6Q0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5aee688828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OBcCicY+DKylF9fQ5JggUpeR/t5p6/JTIxoVTObRY45blbiFFJosGxo9t0izCstyF/aqr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\newAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ae05263c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# specify some cutoff values for the visualization\n",
    "lowcut_a, highcut_a = 14, 30\n",
    "# and also an interval to display\n",
    "interval_a = [0, 8]\n",
    "# visualize logarithmic power?\n",
    "logarithmic_power = False\n",
    "\n",
    "# visualize the extracted trial from above\n",
    "gumpy.plot.average_power(data_class_a, lowcut_a, highcut_a, interval_a, grazb_data.sampling_freq, logarithmic_power)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Wavelet transform\n",
    "``gumpy`` relies on ``pywt`` to compute wavelet transforms. Furthermore, it contains convenience functions to visualize the results of the discrete wavelet transform as shown in the example below for the Graz dataset and the classes extracted above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae0455b38>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae03c1fd0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae047d588>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae02dee10>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae02ab5c0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae0285898>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f5ae03f7668>], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+PP+2U3Ia746ufXbcrMk6zPLth6hrbcDXz0V6kp2YaAsN7gZyaw/T6GpqPz82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MLxcfA+Jfc4FGl1mXyY9QVGlM7rmd0vcanvUi6PSzrh+pVlmS0pFazZVoAsw4PL44iP8DqpchZW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\n/sNM7CcxP21rofIuxPkkEB8RhL16HN3ublJr0thRnkinq4tL4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mobnPz6O3OIjfblT4l/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\nDwSCdPcG8GSkyhb02WYk2364haVWIPpuLVLKcNJHIYQLlUSyDZUzC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S1HOezf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\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LFQXv4v8ao2kiMt12Fk8rYdP+TqrLsmnpjFfeYovhAohIFLkL+ej89/HypiHWb+8Fh4g7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\nsFiSJEmqYLEkSZJU4Q/0v1PgPLXxqQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5aee688dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# As with most functions, you can pass arguments to a \n",
    "# gumpy function that will be forwarded to the backend.\n",
    "# In this example the decomposition levels are mandatory, and the \n",
    "# mother wavelet that should be passed is optional\n",
    "level = 6\n",
    "wavelet = 'db4'\n",
    "\n",
    "# now we can retrieve the dwt for the different channels\n",
    "mean_coeff_ch0_c1 = gumpy.signal.dwt(data_class1[0], level=level, wavelet=wavelet)\n",
    "mean_coeff_ch1_c1 = gumpy.signal.dwt(data_class1[1], level=level, wavelet=wavelet)\n",
    "mean_coeff_ch0_c2 = gumpy.signal.dwt(data_class1[3], level=level, wavelet=wavelet)\n",
    "mean_coeff_ch1_c2 = gumpy.signal.dwt(data_class1[4], level=level, wavelet=wavelet)\n",
    "\n",
    "# gumpy's signal.dwt function returns the approximation of the \n",
    "# coefficients as first result, and all the coefficient details as list\n",
    "# as second return value (this is contrast to the backend, which returns\n",
    "# the entire set of coefficients as a single list)\n",
    "approximation_C3 = mean_coeff_ch0_c2[0]\n",
    "approximation_C4 = mean_coeff_ch1_c2[0]\n",
    "\n",
    "# as mentioned in the comment above, the list of details are in the second\n",
    "# return value of gumpy.signal.dwt. Here we save them to additional variables\n",
    "# to improve clarity\n",
    "details_c3_c1 = mean_coeff_ch0_c1[1]\n",
    "details_c4_c1 = mean_coeff_ch1_c1[1]\n",
    "details_c3_c2 = mean_coeff_ch0_c2[1]\n",
    "details_c4_c2 = mean_coeff_ch1_c2[1]\n",
    "\n",
    "# gumpy exhibits a function to plot the dwt results. You must pass three lists,\n",
    "# i.e. the labels of the data, the approximations, as well as the detailed coeffs,\n",
    "# so that gumpy can automatically generate appropriate titles and labels.\n",
    "# you can pass an additional class string that will be incorporated into the title.\n",
    "# the function returns a matplotlib axis object in case you want to further\n",
    "# customize the plot.\n",
    "gumpy.plot.dwt(\n",
    "    [approximation_C3, approximation_C4],\n",
    "    [details_c3_c1, details_c4_c1],\n",
    "    ['C3, c1', 'C4, c1'],\n",
    "    level, grazb_data.sampling_freq, 'Class: Left')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DWT reconstruction and visualization\n",
    "Often a user wantes to reconstruct the power spectrum of a dwt and visualize the results. The functions will return a list of all the reconstructed signals as well as a handle to the figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([array([  5.21503658e-07,   1.61819012e-06,   3.04630780e-06, ...,\n",
       "           3.08312365e-12,   1.59095105e-12,  -5.12725164e-13]),\n",
       "  array([  1.43090770e-07,   4.44000857e-07,   8.35849420e-07, ...,\n",
       "          -2.05427255e-11,  -1.06004411e-11,   3.41626658e-12])],\n",
       " <matplotlib.figure.Figure at 0x7f5ae047f3c8>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Cq8k5P7iXf/3O9mXsTcC9Rx7kWw/9gAvu/8Zyd6Vh4qbVxw+nCIhNrmd+My1Z\nFpdgbb3z4Ha+vuN7fH3H91K64Jn/7NYJVWb7X/BxLWYWCD+fa3D4giAsAUV8qlY4jcep2vHYaKs7\n0zDDs26Yr32T+5e5J42TZ77yWag0G8Xcif3fTE3tX10PzRwBYM/YI8bzgaYqx1G9jt9AZk1V6PMa\nlCrW4JAFQVhiOkhTVcw/ZMW+WDvAvSVPKPCp2uZy+yefZLG6mHt9TaRqhaP6EghVfhtp0f/983lC\naT0+UGZH9eBojlKsI4n6lC1fPwRB6Fw6SKgq9pZMLKKWzehcbhit9tMBL3knRVhKlDMID7tHH+Gs\nn/8HX9vxnfzrWzhZzSyuVdvmyNhsgTY8oSpFKCrqqF7fuLMd1dei+S/uVSUIgtBqOkioKkZ8Lel9\n0TY+cfu/rmoH8Tx+qH/MJbvTol+0jmpB859J9to/dQCAB48+nHt9oHFphfmvcZXN1658mDO+fAd7\nD2Qn8w40Veavmy9M5QlV9QhCeea9tWj+Cz93a2/0giAsBR0kVBU1/0Vfp6X1bsqUsfnshTGPR8f3\nMbOYr7UIc+meK/ihvqypdotwy4HbuXH/bW1vp+hC3bymKTtXXj19aYZtOw4D8Nih7KjYuZqqguY/\nk4Yvtazx+uBzQaViZyHmP0EQ2kwHCVXFaIcPzaHpI5y9/TzO3n5eXddd//gt3HLgjpb3Z7koqkkx\nlUvzNzKRt/vvtgPb+OCNH+PQ9JECdTX/PJTL2X33n7lSyhgDTVWOdqmOZzcvpMJaMP/ZtsOZ/3U3\nV925z/27TWO++rEb+Ne7Pl94o4YgCJ3L2hOqUl+sjXuKD8+5O/cOz+Qv4p1MYQGl6bUtu4Lv60sB\nuPvwfQVqan6h7S5nf42K+lTlmSLrEgANRSOO2mtAVTU+vcDeAxNcfOPexLlWajJ/+sjVHJg6yPj8\nRH5hQRA6mjUhVEXi06SUaWbz3Vr0TzFRVBNQjxnL2I5/F3PaK7JbrhW3Lk9TZdd8qlI0Vb45s82a\nqmicqsJVrVpKpeh8tztOVV1xxARB6EjWxFsgEklaXFTbRlHzR9W43tevhcm7oqCXXfF2U+gqtUpT\nld2XZs1X0Yjqnf89iE93u/f+iVAlCEJHvQWOzo5w9t3nsX/yydQy7VhLOiUHXbMUX/RbJRzkaKoK\niFWtmPWuoua/HJ+qdmuqwkfWgk9VfAoiQ14L4xcEYcnpKKHqx3uu5NGJfXzroe+nF5KXadsovPtv\nye5BEfP14GoHAAAgAElEQVRfCzRVBR3V83b/5fWkLrOpYVxrbfdf/N4WcQNohjUhqAqCkElHCVVp\nv+QL+VTVEa06q/5GqWf3Wz0spZnHZP4ztd/s4mM7xYSQvFs6v1jl4pv2NNUXAKuUI1QV1VTljKie\ne2ksGfEp6nwBIC44tjuiejMxzwRB6Aw6TKhyyRJQ2vFrciWb/8KCTrsXUlOaGlOTpn7UJ1QWdFTP\nqfO2Bw6yXTe/Y7Oo2a6Up6nKqadoGqBwndFjobrWgKoqoala4vYEQVh7dJZQleIQ3G5HdVON1+27\niVsPbGt5W/USFqraHUfHtFCbhFij8NWAwJDvqJ4tVC0sVsFqwfOQU4Wdq6kKHNXjC3MrheK1lvsu\nPkanzZq6TvCLFAShObqWuwOtJNX8F/68RO+9H+/9GQCvPvGkpWkwhbAAU3VsypTb15ZBaLNth3iT\nzS5oIxNzxerJU361yOKap/TxzUJ5u//csk5E+Kra1aCdegTPmABhWVY0ofIakKqSPlVQGhiGcmVJ\n2hMEYe2RK1QppUrA+cDLgHngPVrrPaHz7wXeB1SAT2utr1BK/RLwX7jL1gjwDq31TBv6HyNFI9Bu\nX5IV/DK1nWrsc3fb2jLNgmnxbvYeDI3PQk++YJCnqWqdH1sxX6g0ocompo0KFauE7l99PlVJQW2t\nbX6LPx+O49D7wp97n///lrcnmipBEIqY/94K9GmtXwmcAZzjn1BKHQ/8NfCbwBuAzyileoEPAz/U\nWp8C7ADe3eqOm/DfofGlq8hW8mYW+no0CEtNdSnNfyZTn6HJZmerpS79LTD/5WuqfGHf/HWLa6rC\nhDVV9e3+C9XhXxfe/bcmfKrS/26HALQWtH+CIGRTxPx3MnA1gNZ6m1Lq5aFzvwFs1VrPA/NKqT3A\nS4H7gKd7ZTYC+/Ma2by5n66u+k1T/s4ry4KeHvf6ru4yg4MDtTILlYVI+fA5n2M29zO4OXm8CBvn\n+mqf43Wb2oozODjA+qHeuq8pQvdc8KLffGw/G/saG2MRNm7sTRw79rj1DPT3RI6tP5oc64aR/PH7\nx0u1EAZO5jwMbFiXfX4g2t+icxpn08bsdnp63K9Zd1fZWC68wB+3ZQM95e5af7pmA0Fq/Ybewn3s\nHwrm/Ljj1tPb1UNvX/B1P+aY/obH2y5a3Z/5kIwzODiAUw7eL8ceu4HBY/tb2t7mY/sZHKhvDCvt\nHgiC0BxFhKqNwHjo76pSqktrXTGcmwQ2AU8AZyml3gH0Av+U18joaGPWQT+HmePA/ILrK1GtOAwN\nTdbKLFQDoWpxsRo55zMyMsWGSvJ4EcbHZ2uf43Wb2oozNDTJ1PR84WsGBwcK1QswFspHdvjoOPO9\nrsbq7O3n8auDL+G0Z55aqJ4imO7hkaFJ5mJC1cRkcr7yxh8ec1izkzUP09PzmeenpuYjfxed0zhj\nYzOZ187Nu89ftWoby4U1iENDE/SUe2rjHZ4Nvl4Tk7OF+xiezyND4/R19TE3u1g7Njwyzaa+9vnX\n1Us9z3RRhoena58PH5lgeHwudG6KUrVquqyJ9qbonisuqLVqzCKYCcLKoYj5bwIIf2tLnkBlOjcA\njAGfBd6ltX4x8DfAt1vQ11zS4gEVMv81YQ5Yyb4Upt1/4/MT7JvYX3OmbxXGbfwGM9NSOfQW81Nv\nrC9h81leDXlxqrIcyKthn6q6+pqsM3wr1oJTdXiM1Wp09tox+pX8HhAEYWkoIlRtBd4EoJQ6CXgw\ndO4u4NVKqT6l1CbghcAvgFECDdaTwOaW9TiD2kst4acedlQ3+6Uspz9EOxe4JQ2pYNr9Z4pT1eTi\nY1nm+2womH++QQetxWrYuTy7rO9zZ8oN5zhOZsiPaqOO6mH/qZoj/Frb/Rd8rlTt6Py1aPzNhGnY\nd2iCPU+M5xcUBGHVUMT8dxlwmlLqdtwl6M+UUqcDe7TWlyulzgVuxRXQ/l5rPaeU+hDwJaVU2bvm\nA23qv5GEpiqiCUi7qomXbAsT3baasKN6dVkc1U2aqrZ2o0b+7r/GqVSLx4/K2v0Xv/dZcarsuiJ2\nJxf7iOjW+TJV5HmsVO3IV7xVw4/EEauz1g9+9kYAvn7G61rUG0EQlptcoUprbQPvjx3eGTp/IXBh\n7JqHgCV6U+T/UnQK/EJvRrBpZPdfuwMR+pg0Ve0S4mbmkvF/2hFSoWhGodyQCRY0urwuVooLOMHu\nP4NQlYj6nbX7r/GQCt4HrN5p+l52K/eNOjz/Ga8vXN9qJKqpcqLPYou+ApVIyJI1IKkKgpBJ50RU\ndyzGPOfcsEMqxBaYlBffUr8Ql8r/IixUhRfodvDNqx82tG/QXi1VEMoiMlWj5r9KWFgtqKkyNBYX\nyOPPZ7VBTUg0JpXvU+VQPvYQADcfvbZwXauV8HxVq1EhuFXPXUToldx/grDm6RyhynKYX3BfcGNT\nC5FTYauXXdstmL2Y1UOWyabINe7C2h7hYil9qkxjMJr/wprDRuIlFYwtlWv+ayKJdj2L8mxlLr29\nPE1Vgz5VkYC3a9SBOjxdi1W7LY76Dd8fQRA6ks4RqoCebn846bn/gjxrcVq3+6/Iy7WI9qwV2Aaf\nqqV89xsd1Ztc3IqKQsXKNTYZEUfwjDFct+8mHp3Y5/Un36cqXlejQnH0mV/6+74SCM9ltepEJqBl\nmqqGd2cKgtCJdI5Q5VjUFkgn+tI0+i/F3n/NhVRIryvVzyty3KHFccJrmCOqt+nlb9Ag5YVUqDak\nqWpNwSYUVbGdZOnlrtl3Y6g9g/kvoamKCk6NLtom899aW/IjPlW2XVgQrodGfd4EQehMOkeoIrpo\npMURCmL2ZGsI6mo3o670JM/xX81LYf6rJtqu2BXG5tu3rTvPUd2UxqZV5EZUIBSeoU6K7s4vhTpR\nanL3X7Pmv7W26IffAZVYnKpwTsxmqIimShCEEB0kVEUFk7TddUV2CNbdcswsYzK9xGlmK3Y9mMx/\nYUHnC/f+J3+/9UwmFloQzdogoBiFqibjJRXVMLVThsjK1xemFPqKNbL7LxpSoTFNVW2O19iaH57b\nSiUap6pV+TrDmqqsZ3lsap5fPDrckjYFQVi5dJBQFV5ErahTamQR98vW7weVRjx+kFPAD2Z5faqC\nY4+Mu/4+Y3Pt0VYZEypHNFXtG3uusNqE/a8RTZXZcT77OQwv2tOz0Q0Ymf0zhFRYbTLVJbsv59YD\ndzR8fZb5z2SWboRqQU3iP3z1Tj73w/s5PJJM5bTWNIiC0Ml0llAV8qmKaBLspAATf48181rLMiWm\nClUJn6r2UM0x//l0lYrEgc2jmKYqvJ41ZnYtdk3eYtVMmpqoz1JGG6Eo6kafqrhQldj9F9y//96e\nm5fcSPDMr57F++jsCDfuv40f6MsariOqqYpGrm+ZpsoJYrNlCfHTXgy38WlXMK4nzZEgCKuHDhKq\nrNBLzYr+Kg2VstOEqibCDcQFpyLmLbsNL3hjO5HghEnzn0+51ILkugZFTDtCKhTV8uVrqmh4f0DR\n4K1h7VQR819W7j+s4vNlMk+uIpmKh4Z1XeUnZxa49YEnI/MT/lbajhM91yJnvqrdmM9b+DqRqgSh\nc2iFemKF4EReTmk+L8FOqGwNQX0tp5tw0jRV+w8HPkztNf8FddfMf4ax5kYfL4RBgDKOrXXmPwcn\nI1Fx9sLZlKYqRWiPE873Z8z9l/McRp8fh6Pjszxlc389XV1VGiqfQzOH6yp/3mW/YNf+MRwHTnnZ\nCUBS8I1uIGmRUFVQUxWnUo3+8Cq1afevIAhLSwdpqsy+U96J0HH3j+v330xpw0hQpBmfqtjiHfax\nSsvX9tUrd0T+bte6Z4pzZNaetacDJqGpWfNfcU1VNo0E/7z9yZ/zkZv/gcnFYo79EZ8q0+6/eCdz\nNFUHjk5ntmc7Dhf+9CEOjQTlVuPuP/8HQNkqpkHde8D1CRwam60di4ZQiH0vWxZSoVFNVfgZbklX\nBEFYAXSQpioUp4qYtijitAsjs6P8bN819L6IyPFGyXJ6T9NUhV+q7UzVEjb/+U7Ppl/pLVlwjbv/\nksWijvz1NxO/t2nLbjt2VX5358UA7JkMzFNZ98+knQoTvxcODvPVBf7phs/xmqednNBUjU3OZ9Z3\ncHiGO3YcomtiiO6nRfu3mtZu/xlpRn8Tfk4em9nF/olaytK2BP+sx4xfqUbvqyAIncHqF6pCb93a\nq8mJ+VTFnMIXqsnEv00lVM7wqUoTVkqhtdZdWNvzYjUF/zT1qV1hHcwhFQIaCf4ZdRLP0FQVcVRv\nQZyqrKkLO6qb5tjkU3XfkQd5aGg3Dw3t5g+e93uhuhwWq9n9Nd7btqcnaj2157apVELB55vGLo+c\na5X5LxpHrHidYaGqjRtgBUFYYjrL/Jcamypazug83ZT5L90Pppryog2vFY7jtFGoKWb+a8Uvd1Mg\nTbP5L6RpqjayuJn95RKlcsbUlHayYDthX5kiwmzSpyoapHKxkh200m8tfC/8Opc6aXgz2C3WVCXr\nb81c2AWfxThVw45kQRBWP50lVNU+xeJUJWL/tFZTk4xTlW/+K8dmvl0v1qKO6u3CuHiFt7o3sAsr\nqglMv76duyojmyIyiuWa/wym47DvVUQot5yIg7OJzFQ4q2jtDr43rYklll5/c0R/tDTmqC4ylSB0\nDh0lVKX5VOUlrXXLN/6SzYqKnVavVQoWC7utmqpkSIX2mf9Mmqrg8zWP3cCesUfNjup1rCzRnXdZ\n12XXaTtOw+a/tP7ECTuqm+c9/nfsB0DMp2qxkrOj0SCDrMbgn63QVAVa0jb5EBL9fhf5DvntVqth\ns2FLuiIIwgog16dKKVUCzgdeBswD79Fa7wmdfy/wPqACfFprfYVSaj1wAfDLQA/wIa31XW3ofwQn\n9CH6oooJVUZNVRPtxnf/FTD/RX2qnDZqqsJ9SQ/+2ag5JNJv04LunR+dG+PyR64G4LXHvTnUpybN\nf034VDUz5ek+e7Fykc/5ZmfHiYaIsGO7/yoNmEudBgTX5aYmVDUT9d7/0J2MRJ+2K7cerrpzHxwT\nREhvePffqhJ3BUHIooim6q1An9b6lcAZwDn+CaXU8cBfA78JvAH4jFKqF/g74Bda61cD7wVUqztu\nJMWnKvz6tCzHbP5rxqcqI05V2guzZEWX23aZqqoGocpk+mjUcdeJiQ1xggTWZjNJTcCtY/EMt5I1\nb7lzWvCeL9oVDs8MNVRNOM2MWVOV3OSQav4rpKmyamXDdcLqcoj2n5Fm4qf58231JHdMNhof7ZHx\nfUwvzvDE0BQX37iXS295JGivwd1/q0jWFQQhhyJC1cnA1QBa623Ay0PnfgPYqrWe11qPA3uAl+IK\nWAtKqWuAfwCuaWmvUwhHVI8sRbGXVl6U73rJjqieZv4LX9++t6pJmDHvEGuPpiqY65AZLDQ/1YYi\nWxe7Pm9MtkMh899XHvwW/7Ltszwx+WSoblNvkoS33Bfd/WdF/o6OL0+oqhHZCFEkVdLKItDQNbP7\nzxOqupNCVSNjPzJzlHO2n8e//fxcFhb93YnF/PvixIN/CoLQGRQJqbARCGfbrSqlurTWFcO5SWAT\nsAXYrLV+g1LqncDZwDuzGtm8uZ+urvpTpfi/zC3Lck1q1aC+wS0bAJgiGjBx46Z1iXo2bOhlcHCg\n7vYB+p4IpnFwcIDZ7olQW30MHpest7snGOvmY/vpG+uO1JFH0b72Dwf1ruvvZnBwgIPVvkS5Y47p\nN/bTxPxila6SRblcohIJT5FcHNZv6GNwcABrZjHoR1/Qp40b3fPrR3prx9LG5h8PK7U2b+7nuPXm\n8v5401i/vjfyd1pZP2XKZGksqHtdD641HNav70m91rGChbaru5wot9AbfTaPOWYdlZkgYnpPX/Cc\nWF2LPND3A765/VW84qknccqvPj3R3rxhfd64aR2DgwN0d5chZAl797/dyGc/9Gpe8KxjjX1fasJz\nU+52f3WUSlahZ91/JtatC+7FwAb3flldSfPf+oH0e5bG4cOuUD08N8LmWlT7YMI3DPTl1rnpmH4G\nBwfYPxwEKT39S1v5/qfeSH/oeyEIwuqkiFA1AYTfFCVPoDKdGwDGgGHADwzzU1yzYSajo8ns7UUI\nJ4utmfUsh+Hhabq9c8MjU5Fr4n8DPHFonKENxaJkx5meCX4JDw1NMjIVLJQjo1MM2cl67WqgwRgZ\nnmJ6Zi5SRxaDgwO5ZXwmJoOX99TULENDk4yOJaNyj4xOG/tp4s/PuoEtm/r49798FYt2MuZXmPFx\nr825oM3pmWCRGxmZYWhokqmp7PGHx1y1nZqOdejoJPaMWRifmZ7PnKfJUJtp7UbKTwblZ2YXQsfT\n21moBPOzsLCYKDc8HX0WR0anmVwI2tn7RBD1v7RxhEVrkZ+PX88t13XzwqdvSrQ3PJy8t6Nj0wyV\nJllYSN6rH12/i7/43Rcb+76UxJ/p+XlXCHec/PvilwOYmVmolR+fcJ99k1A1PjFb+DtUu2Y8eEeN\njXmfQ5qq8YmZ3DrHx9wyw6PBfbJth737Rjj+2PrSD/k0+mNQEITWU8T8txV4E4BS6iTgwdC5u4BX\nK6X6lFKbgBcCvwBu868BTgGiOVnahlP73051BDX7VDWytd8n7rsT8RkqFPxzaRzVg11gzZs/j457\nC3/E/FfUAT5kvnPS+5ROvnkV8n2q3KaLOb2nXOz1Jv26il3h+P6nULJKxlJZO0cBHnzkaORsfreC\n70D82GryqfLNps3FqfI+GBzVW/d9a+z5qcY2HDThjy8IwgqiiKbqMuA0pdTtuO+4P1NKnQ7s0Vpf\nrpQ6F7gVV0D7e631nFLqX4GvKqXuABbJMf21iojolOH0YvLDKTURXCLuSxFNw5IW/HOpQiq02aeq\nSNgCosJVuCnbTg/zUIRqxnW5dTpOLCJ/enJmiDpNO+G0SFmO6k6VcqmMhVUs+KdjR5PrhsyHRfy/\nTEOuCZeryHenFal1Ap8qw+6/VkWZjz0/efi3IB5vrJldjoIgrBxyhSqttQ28P3Z4Z+j8hcCFsWtG\ngLe1ooN1UfOJdqILd/hlZ5m38d+/5yjjj+/mf73ueXU324ijelxT1a5d1aa+NK2pKlUob3mS2cpc\nLLiloV7bXxzN8Xzs2vni7Uevz3BUzxX43FJFSVv2smqo2FW6rC4syyoUysLBiaotwoKUlS8I1Ooz\nOKpn6wxXFkFMtfqEn2imAu+YwfzXsh8xEUf1AkKV9388NEaHBQwUhDVLR32XowJE+gsurnoH2HNg\njGvu2t9Qu8k0NaF+pIQqiKd0aVdIBcfQF2NIhTq0GF0n7qHnWQ9xya7Lo4ueafef4/9vNpc1Eu07\nGrG+cU1VUkuU04nQin1ktFh8okBTlbaQJ5+d6I7KbPNqorZakeR8r1QBykQtpVITvV6wXV/Htmqq\nDPOcWdoP/hmzxYqmShA6g44SqmovuJimKp5QudJi55JEmhqSJrc48ZAKbfOpMvh8NBNR3XEcSutc\nJ9snpw/FxZJk+wZNVDR1Tv2aqkj9GYtjbp1O/M/s8uFl7+hYsDkh7dbZjo3t2HRZGeY/g6YqMqaQ\nIFVk3c0M22Do50pdyv3vVL2aKn+oj4zv47LRC+g6YS+UDQnUm/y6+ffCqldT5RWJ/7ArlVbqnRAE\noR46SqgKFpSoj1L8VWc0GTXxTjPFGvK5+X6z9itipsBum0+VKQ+h6dd/UaEuXio3TpVJkAt99P3b\nGnZUt+NzXzxtiO04scTDeYT94MLBG81XVrzAn+VS2bvh+cKs4zgRQcIqYPKLXm84huEerHCyUiqZ\niAuc9w25+2m6nrYXo7DvZCemziPTdy2DwMcwelwUVYLQGXSmUGWRoalKCxjZ+IKT8IsJ/X3PriEm\nZpLmh8hL1Kn/F3nhvhm0Zqa26tFUxa80f461mWImqflc1WP+C32O+8dFotnXKUTklY9sLgg1m3ZV\n1XE1JF2lMqUUTZXJp8rOmdMsAp8qg4ayrpqWl2qT5r+a0OuUjGbTRn7ERN8p3oe6NVUODz4yzHev\n2xU5LuY/QegMOlOowqktLrc9cJCzvrs9Us4YPqGJxLrJVCNR843pXVuK7Rpq14Jn8qlqxvwXn7q8\nq2qWpxRhp2pwZM/HbEp0/65HUxWtqx6xI5K7LeUyX3gvW2XPUd2Ee9R3+HfipuBSvYJh8pgvmKwi\nRVXgXN/ortDag2ol/BeheR9GY+iKQpoq+PxF9yeOi0wlCJ1BBwhVycXaCgkyX//Zw9HiFlSqzan+\n48T9esILvWU5RsviUvlURYWZFpj/MrRyxsXL9s0dYWEnoFqnFuWJoSlmQ0Es46Zckw9ZGk4ipEI2\nkZAKBTRivrbFFZjMu//8Y34YhYRPVZ2Lf7bflqn9lUk1tFO1ke9GzbznWGZNVQN1hgWfLI1gFpfc\ntNd4vCRSlSB0BB0gVAVEtu2nvuCcRIyYZjFuiw/9Ze5F9BduvbqqOw9u59I9V+T3zaDVac5RPX5V\nAcElVr/Jz6voIvcv37w78ne2piqHWIG8PhwYCqKfR8x/KZf5z2PJKuWa/3xNle040Y0PDftUJTUo\nqyn4Zz0ax8zrHbMvWyO7/yJhWkLZG2rnC/TzyaPJiPcgmipB6BQ6QKgyJeo1m9x8fAfiSC2hl+PM\nXHbqlThxH6XIQm/laQ+ABn6Nf/vhH3L947cU0MYEfbt9x0EuumFPU5qqegXIPPNfoGkq1r4b3yd8\nfVxzZhs/m3DHUnxR/MnWR2qfw0FH067yTVAlq+Q+BxnzXjP/hUzXQN1m6drcRrQqvoBRV1XLSjRo\nbXEByJ/jmqarhZqq6PWmY437RWYFnRUEYfWw6oUq46IeF2RiL1VTnCqf67c/wQf/4xbu3T1UuA+J\nkAqxLfEmDUE06nrjXlV5C05YgKraNlff9XjDmirHcbjpiVux+vxf21Z0ccna/ZcivAQhF+rAJDDE\n2ou3U4y88iZhMH2BDmuq8iKqR32qQrv/SvUt1OZnLXkPavXXVXvrGJ+a57vX7mLbjkOJc6OT84V2\nV0aJjqRaM/+1zlE9jMn814yfVjMZHQRBWDl0zFfZtsPmP7Mg45PlqH799icAuGPH4cJtZ+dvcxLa\nFPdo9PpGX/Km6PCpfbP8xbV48M/wcT26hyv2XUWpzw986cTqMplZ/P/Nwo5viU2GpSgmTFRjbdqF\nTMChvhkicKdi8qnJ6pvvU0WpuKM6sd1/5Qp95b7ctmq1ZQnMK0hTtX3XENff8wRf+elDkeM33XeA\nj5y3lfnFkN9cs+Y/Y07KBsx/ERN2cDQ4Vmc/uxbofdlNlDYfkt1/gtAhrH6hynuPLVbsQFiyMsxp\nlpOZPLlcdl9uWdqsOLUcY96qGzffmBbguDNyo+aIvHg7cTMjwEIleY1JqHtg7zDv/rcbeXjfKAAz\nldm6+xdoScLCTnDeNsSpGpkb5UM3nsG1j92YW3/CUT2sASzk71WHZivilJwf4NUvUyp5miqDMBv3\nqXrs4ETU+b+8yLpyf3a/Im3WPoWOOV5bhatpO9UUv8Zt3o+ZxdBmkkbMatVcn6r6J8MYyb9On6ow\nXVsOUOqdo/d59yGxPwWhM1j1QlXkRRZZ9NKvMQtM/uLmCVV1rED+Qu7/2oz3ySxURV/G7dJUhTU3\nvt/Y/IIpwnSy/Z/c9igAV925z70+YSyyjJqwSPu1BT3F/Od9DtezY1i77T9yVXJAXg1p/c5KpA3w\n4NGHuOfIAym11mH+y2kHYpqqgua/q+7cx/BESHjtWmRdeV3hcAgmn6qwr2Gy/eUhmmA7+OwLF0Wy\nEmTXn7P7rxHtl+G5qzeieoSuRe86iVMlCJ3Cqheqor4Uwa/HrBec2fzn/teQUEXGwp4SpyrhU9Ww\npqq4+a987GG6TtxtXFAa8wdJCoMnbFkfaz/Zj6ijumHBy9NMZPhUhYVM0zi//MA3+dovvuNdGzuf\na/4Lmy3zdxn69ZetdPOfEyoDYK2b5MbD1wVNlhzP/Fds0Q2mMznfDoWraTuR/JhhoaqmsmlcAwTx\nOFXZ7Rcl8p01PKKXP3I1l+y+vHB9tUTPlR7Z/ScIHUIHCFVhASY4Fl2roy/QrIjq/ku9HvNfcvdf\n1LRnEhzs2KLRqJNrNc/8F6u3+8S9BXYjmjG996OO6k7CjGHO/VcNnfdjZxU324XvZ/xeRurOG5ND\nneYbszCYNnd+XyzLytBUufiaqu4TH0mU6S33FVYpGcM2RHyqVoYNMDx/4RAn/o8aJ+wAXo/5z4ld\n45illfqCzfrXGO55TAt24/7bmFowh02IY/maqkq3aKoEoUPoAKEqoKaKT+z+i5YzC1Uu/i6cepIu\nx1/64ZevlWL+S5ipGtRUZY3F1DdI7lYMOlEfDklBJJ4Y1qSpGpqYqX2uzU14OuqYi6y8i3kLZ7yZ\n3MU7stPL7CNm6kvJ01QZzW+RAKFm+krFNVVmrWhIU7VCCPezEvoBEwgXzcWpyv2x0ZBJ0aRdS9az\nY3hnah1dJ+yh+5k73Os8TZWz2LNSFIiCIDRJ13J3oGVE3kpZcaoc9yVejl/v+0j4mqo6FvaYX9DC\nYuiFbtkpu//CC3T7QioUyTeXdixB/Nd0QvPhJCJD13yqQovkgaNTdJ/ofq4aNFn1zEU1IVTVs/vP\nFQtr5fOUFykxo+LNHJk5ym0HtvGi4xTgh1Qwz3Hcp8pEX7nPoHFJ60t6G24E+ej55VrMw3MR1VQB\nOJkm3ky863J9DRsx/0W0rX57yXpG5sZS6+h++h4AyluexCp77wnRVAlCx5ArVCmlSsD5wMuAeeA9\nWus9ofPvBd4HVIBPa62vCJ07Bfiu1voZre64j9EJNxFwM3quahuEKo+ylW/+Gx6f4wfX7+YPX/dc\nBo9Zl4jFdP09+2GD355ZwIs66trt2/1n8p8yaLeGxmfg+NRKAPMCHA90mtRURQVOt1zSCTm6YGUv\niFbENBQz7da7Uyy8eNdhErIyzIbn3/81hmaHOTLrxjqrxanKCGWRJVT1ltYZOhBtc3xqnvXrums9\nsSt241AAACAASURBVAzmM8dhxewyC//QCH/X3OcnOrZGvhvt0VQZBHZjXsH856gmUAGO01EGA0FY\n0xT5Nr8V6NNavxI4AzjHP6GUOh74a+A3gTcAn1FK9XrnngF8BOhudacj+O82KypENRqnquZTlVHB\n9/57F9t3DfHta9xdavGX7eNHJiP15pr/aDxwYCO/yI3HCpk7YwJT6F//SEKZVbPuhYUqg29KAfPf\nQnWRnhfcidUzHyqbHng1b06TKW4cDg5Pc84P7mVoLBk+wpTb0G0z+revqZj0fGvciOppvj3uxeUM\noaqn1JvUVIUE04npBT78pa189vv3ZmuqSFE2LgPhx20xLFRZyd16dWmVHP+aHA1uAcHnrO9s55tX\nBaa8vA0WQbn6BPu050oQhNVHEaHqZOBqAK31NuDloXO/AWzVWs9rrceBPcBLlVJ9wJeBv2pxfxPU\nHFpjLybHcSK+GmFMmhr/bewvOlk+VQuLVbBsZhZnvLbi/h9RrUyW2Qf8BaA9QpVJU2W6JtPkZkX+\nC1+UuCrN/BdNvBy07wuvccd9Ew+PaMobRyPH4ua/ah3mPydmvnQc+NqVD7PjsVEuumFP8oKY4G76\nGMbXIpbwc/+Z5t2lZKWoTvGEsoRQFQjrvgC4+4nxTJ8qHIcM2W1JCd+bsPnPKiWFqnrMwX7JQDuX\nIszmPBszc4vsemKcW+5/0tiP2uUZYUSKI0KVIHQKRXyqNgLjob+rSqkurXXFcG4S2AR8CThba31A\nKVWoI5s399PVlb6wpFHzRbDCi7bDhoE+Nm7ygibG/K1K5XQbSF9vt1cKBgcHasd/fPMeTtiygd94\n8fH09nbT+9JbONQ7x5Yt/yNS35YtG6IvWsth08b+SF0ApVJQZsNAH91Hg7HHy2ax6Zg+Bo9NL9/d\nk5zT3r6k8nD9+t5Eu93d7grc09PF4OAAmxaiZqhyV4nNm0OBKS2H3p7oI9Xb283g4AADC32Rcj49\nvWUGBwdY93jQp/7+ntrncJ82bUoGwexf3xMpM0zQTk9POXUuBwcHWNfXHXk2jtncX1veurpN15q1\nbb19XZGylmW5bkHec7FxYB1dR8ssOFaizoG5XreO7vSv4vp160iItJbDluM2UC6XGJlZrB3eMJCM\nvu7PUalUolSKhnbo7e2q63lrFX2hZ3DjRve5GhwcoL+vOyGobN68jsGB7D76r4G+Pvd5o5QtqPSu\n684c9579gV/UwKZ19PV0sWG6t3Zs/Qb/c7KdvnV1zqnlLMs9EASh9RQRqiaA8De+5AlUpnMDwALw\nauC5SqlPAscqpX6gtX57ViOjozNZp1MJfv1HtQjj47McPDRuuoS5+Qr0xA76Giov2vjiYpWhocCM\n97XLdwDw9TNex+JildKmOQCePDzCQiUIpnlkaCJareUwMjrN0IaoIBPWoo2OzTA3HyyM4XZNhF/A\nQ8MTbKyml5+bW0gcm56eMxybT7S7uOj2cWG+wtDQJBMT0esqlSojI1ORY9VKVBszM7vA0NAkY+Oh\n+xtOXu2dn5kNTHqTU0E7fp8GBweYnEj2e3JyNtLvkdGgP3Pzi6lzOTQ0yfTsAuHnZvjoFIveJoOF\nhUry2hQzzeys284FP/4F63q7wJM9FxbdezozvUC16lCt2ok6x71An1kbI6an543mvyNDk3SVS4yO\nBXM7Pu6bLYP6pqbmGBqapFKtYsX0PvPzhnHmcOFPH2LzQC+/f+pz6rouzPR08FweOTrJs0/cxNDQ\nJAuLlcQ8Hx2Zojxn8CtLqXdoaJLFxeyk6DOzyec9jH70aO3zw3uGePrgBsZDu1b9+2Z6JqZnsutO\nYDl134MwIpAJwsqhiFC1FXgLcJFS6iTgwdC5u4AzPXNfL/BC4C6tdU09pZQ6lCdQNUPtlRYyKfmO\n6oGvRsxElBWnyhD8M67OD1u4Zitz0cCW8faslDhVEf8Mm4mZpPBThKrdgKO6ydxQwK8jYTJxouOw\nLCfpqO7v7gubvkJJgk0JleuJIZT0iyq2Fd9xkrZLG7tm1ombMYGEBjJSF/DznUcA2HiSe9x3lg6C\nf5p86/yQCulaWsexcJxoPHsrHODW5I9mJY+5kbtTm0lw0Q17eMqx6zj1V06M1HWHlwS5GaEqfN+q\niThVcVN+PTHj3Gt9M3BaQuq8Og+PBj51Q6OzPH1wg9H8Z/KHKpy3cuSplI89XOi7JwjC6qCIUHUZ\ncJpS6nbcV/WfKaVOB/ZorS9XSp0L3Irrn/X3WuukOqGtJBcRvJAKRmdSy+xT5L8c/UUnvCMpXk+4\nqdnKXDKJb2Txzfepqto2syFNVR6RwIl5QpWhbZNQmelj4g04ETneUDTpU2W41rB7zxhYMdGNpEQQ\nX8CKhlRwSEaxt51QL/wxF1ggk614OSBtP32RG1LBKFR5/2c5qrtaqqSmyvTbIBhSaI5Dn+PNZMlY\nV9/1OEBEqJqdz37eihIN/hmOU0VTjuqOA4+MP8bw3IhXoS9QWpk7NuNMhDRp497ntCjwyT4U669j\nlyN9FARh9ZMrVGmtbeD9scM7Q+cvBC7MuD5to35riWmqbMcx7uArWdkBM/33YdhRPVzPzU/czu5j\nf1r7e7Yym8xrF1EppKWpCdXv1BenKvzCDyeeNWESCsxRtwsIDznCISQjqptCKlimkApOUgiIC1Gm\nWD7JXZTFNFW2Y2M7sdAITlCf31Zk/nI0VXF84b1sZeT+i7VnwnGsTEf16LjS28iK6F6UqdnGNKqJ\ndkMNV2K7/+Lan3q+GzYOP3v0v4MD/rMWywGYJ6hFNGk1bWro2fLfCQ2GVHALlhKbJQRBWN2skL1A\njeO/cOMhFRzHfRmWjztA34u31c5YOUKVH24hTVN10a4f41iBIOOa/+Lakfo0VbZjXiDTGJ0MlIHG\n8BAp7QTtGaKsZ1Xja5sSkeNjC7UhTpVJExVZ3GoNJ4WUuKDRrKYqIrjF7xOBoAVBPKd4yiET8VtX\niwnuhDRVabn/CoRUcIWq2EHLThHWY50gEAac0L95pD2Pk7PFNapuPTaHpo9kRr6P7P5rMqSC48DT\n1j81OOALVXZ0fvMENVMcrejzE9SUuDa1v4mbmBD2BEFY3ax6oSp4UUUXbcdxfZl6nvNgpHTJsswm\nHe/F5vt3hP08sl7qs5W5hKbKimk08iKqV+36gn+OTgRO3bk+VUXjVBUxc8XLOPGlKRlRPdjNHxU0\ng3aT52tRxgvE+84K/hnvXXiMYQEq6KtT63Atsn4RTVW8U7VrQz5VOZqqbJ8qSBjqSoF2M/JzIlNT\nlawmjbQ4TAcnjtJ1/KMUFc4u23Mln7rzbO4f+kW0/ohQFddcxp+qOnzsbIdyeC79++TEn8uc+G4G\nTbXR/NeETxWeBlLiVAlC57D6haraL/P4i9gcwLNUyg7sWTU4TmcF+purzEVeol958NtYfUFC1SK5\n/2zbjsZpyhGwxqcDoWoxR6gymSKMmqrYsbH5cebW7Y/VZRIOo9elaarSzGi1eELhOlM0VUVMmVma\nqmgsLNtrNLpQBg7I7v/hyNxxbWhaO2maKqNWo7ZBIuOraCfNf1Y4/VGoWpOoF/GpKriAp31HfnLo\ne3T/kqZ87KFC9dxx8G4Ado09Ejme5lNl244x5lwe/uw4jhO9Z76jeixqeW4KI4NQFfH7ayT4pxX/\nUeL5yolQJQgdw+oXqvy3aVw7lOJTZZWszN1/pnNZQtVsdS7yst01uoeupzwRajDFoTiymNtGTU0a\n4dyC1RyfKsdJ+nQVifB+1l1fYGzLHVj946lO2wmlgmn3n+Ned+/QA6FySd+UqGnFE0bIF6r01A7j\ntZCcx0i0dcdzVI/tkvPnJi4Y+TUaiR32+x3VVKXsuvTayzf/JX2q/GHnOVBn+VSlkfbMz9je1v/u\nYr5V/pzHxxf1qQr/wEgKVfWa/yKbNyxzENB6ou1Xjc+oX38xTbCpbO2+xoUtQRBWLateqKotnAaf\nKtPCkJbYtpaINRYvaMfwTu4euje1/dmYpipZb3KXWaTfuC/tiFCVs4hUqkEMHtPuv91PjNWc2R2c\nxIJs1lRF25xcdOM9WT3zIZ+qpDYwLrjEHdVt22Hbwbt58OjDwcG83X8p2htTv/fN7uHBow8Zy2Rp\nsUzmP5uwpsrkqB4qbEUX2OjcRK91jX+lzOfAyvgqGs1/oecq+uwYrvfNhHUoRLK0uV6lxeqpaevM\nGkyI+i9WTZqqOsx/cU1VYP6rU1MVOu3/0Ers8g3XH742rb/xso4hUr4gCKuaVS9U1TCYDExJkUtW\nmibI11RFz51//9e59NFLU5udrczmhCNw+P71uyPaJbd/0QXeJFSkEc6VVokljj04PM1nvnMPZ/7X\n3V7dxX5JF9EGGBMCx3zZkj5VDgemDkaORdLUZPh3JRbilHnxc+259RXzqXJwmLVGKK0PAsSGNxnU\nzH9hNWMsan9A1G8uMB0G5j9XJkrXIhnjYtXKmDRVNn93we3uJodQ26bFviZ8xY5nkStUFcSuaarK\nseNB/YveDxn9+Kgb6yumuSn2bPplY36G4d1/kfLZdVZN5j+jRjD9+U1gMv85JdFUCUIH0QFCleHl\n5plGTAu2G24h/SVWNS1QGVTsSvYWastmdHKem+49YOy132YygGhGmyGTX9xR/eCwG/V5aMzdIWg7\ndiEn3SLOtUXMhlbc/IdhATNoqiKaizTzX5r/WMSElwzXYPrbdmx0/+Vu8MXQ+dpOeZOmKmP3X3Qe\noteWLT/3n0mrYdbKReq3rYT5CsuhUnVYrNiR59z0yNaezwbNfw8NayYXpjJKu9y3+ygPPjIcracW\n3DSmdTTsrvu377ka4URIhXqCf+JQcQJNruWnq0loqnJ2zUb6l9SmZpn/Ut8bCU2Vd1/Fp0oQOoaO\nEaqsUK4vy4LvXqe55Ma9idIlK+WlV9v9FzNF5FC17VzzH8DUXDRthmMFfyc0VTmLXzg2VTykwlRs\ny7tj2PJVn6bKqV2eXIhi4pJBU2XbBkf9sBbFEFLBFxTjmqq05NHh6qsZQlBY+H14eFeinqsfv4Zq\nt5tmKPCpMpiSYnU7RJ+VuM4pK6RC7fnNMv/ZyXvoazds24n47GX6VFGPo7on2PaPc979X+NTW7+Q\nqzE690cP8PmL7o+2nbKTM/zVSiQ+rzNOleM4WMfvobRhFNt2zDti7eZ9qooGlk17HyTmXhzVBaHj\nWPVCVdbr6PEjyV/XlmVlLg7hxXGxkq+lqDrVzPqCF2lsoSgFwk/ViWuq6hGqogvIdE2octgz9igL\n1WRcoaIBQUMd8q6LaxBi11kO5YSjupMUxkpJbVLEx8wTZBzb4iPnbWXfoUmu2baPx49E8yr6PBG6\nz1mO6uFz39l5caKe3RO7WXz2Le5QckMqRMcYsRLGBAjXSTstTY1jvCZaJhmnyn+u4jHOgo/J56mR\nkApWr6vxnHbGuX/30VCJ+nyB4iEjws/NYjzvoTc232SY9v2aX6iya/8Yh2eGKJ+wi94X3ek6qjtJ\nocpx4q+6Js1//vwYfarSNFVx85/rUyUhFQShcyiSpmaFk6FqNziBWim+LTVNVaZQlayv6lSzhaC0\nF2Y5EHZsu3FNVfxXua+p6h48wOfvucarMHqbi8auAiJDNpk5kxHVkxqJLE2VKU6VL1TNLVSZnpzn\nkpv3suPREcqD++n55WQXZ+aiWr9abxJCYIHFq+S27cuGYVNSdFGMCjLRWGVRrIw4VWnR46P9thLm\nK78v1arD0NwhyscepDrytJBPVfj6pFCQR/A9CK7JCvyZp8WK7/6bY4LuZz/A4uOqph221o/hzG6o\nja2rVKZarab2+5tX7+TOhw7zR78TBPt0BVyDpqrAZo208fgBak25/4rEqUpzag92/4lQJQidwqrX\nVKVjflFZVvYCkCpUpbz4qk6e+c/f0h3rXUiocpxomppcJ9qwiTLWtr/wdR8T1urkmz6KLLjGkArh\nViw7kbDXcZyEMGZMUxPRVPnna3ZH78+w2dAshER2+GVoqnLxBhLW9FkGTZW1bpLd63/CvsloTK8w\nbkJl830N5j39q2iMABL6EfDjI9+m57n3Y/XMZu7+8/8ytx9vM3k8Sze1uJg9t3FT7pP9t9O15Um6\nn76bStXh3Cuvp+/F2+h53r21sXWV3B8DaT6L9+9xNWePHpysHYtoqsKCaEwozUslYxt8qmyjv57p\nnqZ8T0zmPxGqBKGj6AChKkNTZTqc5lPl1RPNq1dAqLLTf0kDWL0zdJ2wJ+qbAxA2/9UZUiEc8DOu\nqfL7312O5CmJUF9E9ax+xUx7hjhVtkNyF2bazjT/Gn9M3sFaHKPwPbDNStbskArFFy9/UV20Q9oZ\ng6aq5/nbmS+Pc9uTW4NisbpKllXTRKUmi87YWm8bgn8GmqqgT1b/RKh+wxzXYf4Lflxk9Cs0lrnF\n7HhpCf+4kpdqqVyhUrW58SE380F503AgVFldkf7HGejvBmB6LqT1dRyqdgULK6r9iwtVBhNh5HzR\n3X8F4lSZw74QCFVF41MIgrDiWfVCVerrqJSlPUo3/4UppqnKNv9ZZZvup+/hgPNQ9EQ53VH9g/9x\nC48eNPsPQVSQCn9+dHwfk7a7+yqyhhXa/Zf/Yk8ubjHna5OjuuPw5HDMty2sqQrsf7VjQZwht66K\nKT9gNfDRmbYn2Dmy22uvmKN6Hv58RHzSSsnnoeT5HA32PSW1rpJVdsMqkNRW1e5FplDlJM+Xkubq\nUv9kpsDs4MTvWGqQz6xYbl5lkWvnFyqJ4tseCqKuJ56d0J+Vqg1di1654GS55PtUme/bQH8PANNz\nQYYBX1PVVSpH5yw2f9U8TVWof6aI6uGx95R6YtemaaoMPlXiqC4IHcWqF6pSSXlRxYNTZlEpoKmq\n2MnFxMScExMsytFf1/F4T1fesS+1rohPVegFfvb28zg0eDUQX7yTzuNx0raYh01ecaHEIRbY1BhR\n3WG+EtMKGOo0mf98TYOvqQr3pafcXfu8d/FevnjfhSxWF3N8quoQqoyaqvTFL2u+L7vlkVp96alz\nciKqx+r0TahDY7M4C73usb7puoN/psnSRXa+hgWLuYWk5ucrlwc/JNJ2boJ7fy3/R0a1u5Zapqap\nSvnRMrDO01TNB0KVq6mqUra6iDqWRedvanaez3xnO0fGZo115+f+88ZjObV+1s6lmFiTDuli/hOE\nTqMDhKo0M19aAL7i6vYimqrFgkKVTWzRiTiqO8QDaya2mUfOpe/+88ne8m3SZqQUNuTpC7cRFQZt\nSrEnyt0hGDf/hQQfQ67Fasz8VzNxha5b3xvVDoCr4apm+FRlLeyxXtcW1Yimykp/HsIaw7hf2c59\n4wyPz3s1mxfcUq5PVewGee3/6OZHajGsrJLN44dd/6ITB9cn2nAM/U7TUNoGR/Vk2qCQpipk/jNp\nv+LmtmAeLPdZ974PTqWr1mbe7j/fpDi7EJjsI5qqUH/ju/8Ojkyx+4lxfnRTMuxKvE3/+YvGqQpM\nelYiBU88eCm1stGCEqdKEDqN1b/7L+2FlOFTZXIT6TruEPbUPqqHn1k7ViSkQkSTEcOplrDKXjyh\nkFBlO3bC/IcVXnScTKGqats1cbhm2snwH3Kc6HKYv4svhMGpPHxNXkR123Zw4vcioqmCJ49OsxjS\nZsW3xJt8qkzBMt0cii3wqSpXamXD9zepaQj+jgq3cW99b+dfMjJCbf6y4lTZJqd8ry+u359VO3a3\nHkr0oCZcFtRU7T0wzt07h5JNxtL0RM1/wfh3je7l8keugu7nBH1IE2gd9weE1RVoqoKQCtmaKv+Z\nqcbuedWuULbKWE4luDI+h5avPTJ3y7Yd/J9fZp+qwCSdl6My2P0XN/+5mirLSzkU9zsTBGH1sfqF\nqjRSNFWpIRWAnmc+zOzhZwIO5ac8zujcL4euM0efyTT/2WWoCVVBf+YqC5GXue04OBEtSDTJbKLN\narUmVPn+R3GNmSnCt0/VSfb5/r1H2ftL4zznxE3RExGn8vgvcCcylZYxTQ01gSIoF3xerFT5xFfv\npO/5w1jHRMfkC2M1ATMsVBGNewSuMJadpibbObnWv/JibSFdqIYSB8cd1UP9MQacrBW1Ap+qFN8i\ny0mOp1bEhoSgFnZUN/nsGDcDRPscPrdYsenucvt45n9td0+WF9NjKFlORLsZNv99+cFvsGgv0nV8\nMKa4ljCe+5IeT1Nll2vjCDRV5u/yvPejp+JUaiKp4zhUbFdTFel5TFPVddwh7LEnKVlPjRwfmZjj\nkpv2cnR8ju6uEgsV2xj8M6Kpygmum7b7Lxwqw3bsRCofQRBWH7lClVKqBJwPvAyYB96jtd4TOv9e\n4H1ABfi01voKpdQvAV/36reAv9Ba6zb0n1RTXp2aqjDlYw/R86yHuXIoSGGSav6rpgtVjl3Gwl0s\nwpoqf6H2NVm246RqqhzH4d7dR3nu0zex0XPMDeej8z9XYhqzyIs91vVFJxTOwba8aPSuH9df//5L\no4UjWqVoRWOVo/xAXxopG09T4/YjXUBc8LQNtuPUxKRAUI0JVaF6TAtQ1a7Ggn9GWYz7dqVRsvN9\nqiwnIsRUQu0mY06Fj8QEvZoWKUNTVU1eR03gdBLH4qUzfaqAO3Yc4sKfPsTf/sFLeelzttTOrfv/\nrk/tkxXXVIXMf6aYW+m7Sy0WKzZW3/9r77zD7Djre/+Zcsp2rbS76msVS68ky5Ity8Y2cgPbgDFg\nQm4SwDhAIHCBJARSIIGbm+cm4d4EuCTxTQIEQk0CgRATCOAkxti4d1suo2L1tquy2tXuaVPuH9Pe\nKefsEV7H1vr9PI+tPVPfd86ceb/za29YRd+VLFVG0O4mv71GeO/bhM5gvy6aQ8EopQLVs9e3uPJx\n9KlNiWVfu3UbjwalGjpLZkJUJd1/0vedmaOy3ZIKcZtcz8XIeVFQKBRnFu3EVN0AlC3LugT4CPCp\ncIUQYgHw68DLgVcBnxBClID/BdxsWdaVwJ8An5jhdkc0Ha5/BktVtE3Rz+gat49LC5u5/1pYqqSH\npmwdigLNvfhN3NPTLi+//c/sOcHN//wEn/yHR+J1cvZfYH2pp0RVq8DphACT2niqmuPKlOOfcga3\no9XjiW3TiQCZuKsUcbxUvGyyMZVsb677L0dUeW5iQEu3t97CpZpAElU1u0n2X+qzbKnK9FYKNM9a\nMYIB2z3dOlWBpSpRyj3422hwuBrPNZkoqZA5tscP7t0LwE8ePdi0DZn9NS8RzJ4XqJ44T6v5Nh03\nvpa6kxFVzfYNBbl8Xzy95xhV284EjzfLrkwnVlRqdmKdoWvRNc4rqaBpXsZ1m6lTFZkj89x//r7t\nx/spFIoXM+24/7YAPwSwLOteIcRmad1FwF2WZdWAmhBiB7AB+DBwUjpHdeaa3BrP84VTcfmTOGMD\n+RtNFxjaZskFmMb9J6X9h64n13N5ZPTxYKEeHMNJuMS0YLJcgKPj/qXbPzoZH1YazEKBlLaYeZ4X\n65TUgGIjubQcAwx/IJucyoqqRPbfdA9+zcPQ0wNM66D5eIqSeJvx+kRiWSQcpLakK3RDOGWQbKlK\ntreVVTGBFk9SfOfWfdAXLw8x5x2Ovr/w3NHu6eN5zS1VYRs9p1VJBWn74P4OvxfHlVx6wb+l9Xcl\n9o9FbXP3X/Zz9jtLCsJk5mdtmjpVzdx/uqZhu5LVT3ejvulMF1OVTWBAd6k1GhideuK+z05TQ3T+\nZLukdbqGrmuRwJYFuyvdk9l5DfPdf7lz/wVtTN+rCoXizKQdUdVLLJAAHCGEaVmWnbNuAuizLOso\ngBBCAJ/Et3a1pL+/E9P8Gczf6QeVq4PhoneNo3dlaz0VTANaPsCauKuaiaqc+KToSG7cH0/zGBzs\n4fZd93DLs9/3l3n+41gzs+2p1h0qjkdvT0e0bHCwxz+nlP3nGQ6Dgz1UxuS++vEuzWwfDnI1dyMa\nEio1/1iPHnoy3lhzKRQMBgd7KO2f5nbRPHp6yslFukarUJH8KXOSIiqvpEKpUPCd0RJ9c8oUR+OT\naboWXTOAjvFsxmBuNzQX0/D7PFmrRT+S9KBoDsaWHaMQD6x6OgUSzb+3bZg3r5vOYvyddh7x21Qq\nlRJ71KxNlMTD/nkKpu9cB6IUfGlC5bBdmu6Cbke1s0KKRSO6DummmQWDQsEJtjPp6w+yBnMsvZ2d\nRTgWdsljTn8Xg3M7g2ZlRaEmWfJKJSPxXYRb66E/PhKGbnTujiDDs6u7lNg3JLJg6klRheZSLhal\ns9DUUtXVWUwcu1CI7x/T0DENnZETFe544jDF3vj+L5SMqL0FswiyQdNI3nfFU8GN2kJU9c/tpKfU\nndtGhUJx5tCOqBoH5CeaHgiqvHU9wBiAEOIq/Fist7UTT3XixNR0m+STHpO91qLJt3q0sFRp2bf5\neHn2uC3df5Kost0Go6MTbD2wXVrvj3CnqqlaOZrH8fEq7/+zH3P9pcuixaOjvgVHtopU6lVGRycY\nGZe0rfS2D2QtVV49Hm+CNmiax/hkndHRCf7kjpsTbanWbEZHJ5icSqmYNJrLVLSNh949Rt0u4bmN\nFo7m5t9FaKGw7aylys2x7IweS7ax3mhE1wzg+InsBNu56C7VWrCv7JZtVqYDqEgFKDMlBTwNx/aX\nffX7W/m5LWuiVacm/f2mJlP3kWRZqVbs1PLYRdZwXHTJUqWZWWtjpep/r66btaLUanZ0fWs1m737\nT/grcornfuG7T6KfT3SuB3c/wZrKUnqLPew7HIv6WsPxhbR0vSYr1cR3EYUZaVCt25EA0yT3X1jN\nYmx8MrFvdF3CgqPSefz9Xf/+kLvaxL1aD+7tkEbdxhg4gFY+hTa+AV2DyarNl77/FBuvGIu2q1QC\na6/ugqNxycILuefQA/4x7eQxT4azNOQU/wzLYYwcHadanMaC3oQ8walQKF4Y2ompugu4DkAIcTHw\nhLTufuAyIURZCNEHrAW2BoLqz4FXW5b14Ay3OUmeparV5jmB6vU9a6QN3HxRhUd5409yl+fiezFt\nPwAAIABJREFUkQpEzcnSC0WVIxv7SDx8R3LEphxH0/Dq2eNmBv90NWlp4HViXZ1fRduTYnJauyjk\n7D9j3kFK6+6jOvBYtkZXXtOaXPP4/8ltlpSXZbZ2PSdy0RT1AjWnxsFTh/nSk/9Ixa4kiqa27kgc\nhK2lrSBNkIVuLRVf5HkajUBUfe+e3cl1oYvTkV1VJIRwIhQsXC5NqBx935KVR8aNrmP2GqcSM+OY\nopzvIxGMXqzyle1f5vu7/h2AY+M5Hn4jv0itjKZpfgKB5P4Lz13QfOtds7IlofsvUZPOsEHzJ2P2\n5JcJN99cmo6pAiiueILCol2ggWFI4laqGu8GFm1Nd9Ex+CXxRj564QfpKXTnzP2XjQn0l8eWqtOa\nl1KhULxoacdS9R3gGiHE3fjP33cIIT4E7LAs67tCiL8A7sQXaL9vWVZVCPEZoAh82fcAYlmW9Z7n\npwtJQpdaM8IIBhnnyDKc/iMYvScSD/XEfpqHVpzGUpM+kxxzQyiqpLpHQbbPqJuqni4N3nm1a+RA\n9UYUU9VsjjrAg+qjl1Pa8FNfJGh+YLQ7Phf78DJKax6keRZlHLTdTkxVOEjp3f5bfaP7ICZdrfZq\nebxMR4BlY6+jd6gzs7kcU9VhlplsTPHJ+z5HTTvFYMdcyk6TGLs0ehxTFVqqPMdAM5qLMlk0VOsO\nuuzNkwf3nEB+SFnepABmCGKqopoBwR9STFVBjqlKXzPH5NmTu/2MUw8yMV0pVTVVy1p/8tCKVTw8\nTtZ8C9Wxk1lRpUlWvma1m3RNo9ZwU6LK/9vUfPdfogBr2C03zspL/F6C+m+GbiS66jUVVcnP8tUx\nTAc32E/vP8yos19qf/yc0DAwdZMlPYvQNY1T1To7D5xk6VA3n/j6w8zrDVziee6/4OI7udkICoXi\nTGNaUWVZlgu8N7X4GWn954HPp/bZOCOta4vnbqkC8BrBKKg1i6k6vYeeJpn2/VZmLVV6rRevayyz\n73QZd7J7yQ7KIyTEmp52cWp49U7csUGMuX6ZCHdiDvVtm9E6AjeF7ls8MkVHpXpE0xbP1DzM6M0/\n+NesU5ED4zM0D4zOWFaC61KpeRg5YlMuqVA2OzhZn6DhTfouJqeG0WZJBdP04uDwUBg4ZsLykjl3\nyxpYOVU/A2JLlRcFoYOWuHccx41/qVL19PjwUjxSypqmj53FhLGTLzz+j3gsyQzssqeyYTuRparp\njAThKYMK6FW7SrVuc/KU9B2HbddTBW7zjqNp1OpOUNYjeHkJ+lAMLVVO9v6pN3L6D1FRXVMzk2U5\nmzwXWt3SmuFg6P6FL616FNlJ70jB9XI1fM/TmJiq88dffYh3Xb+WPYcn2HM4+I01Kf4JylKlUMwW\nZl/xz2lEFamSClE6tBfGFjVx/53mVBIaesLl4AZ1qGSLkul0URlZijm0L7mvHleEyisCKg/gNnVc\nz0vVU3KTwjHMMMpzhwTLzKF9mEP7uO2h1cm2aB6e09x9lNjWbHDc299ym+Y75y1Miyr/81TFzq2o\n7nhuNDh1mr51IBysofmUPpmm6JL7z3DwHCOoOdYcNzFNTXxOz9XALkRV0TU9m6UJ0LDx70HNTVgw\nIJntGVliEzWzQjdYNu5PP7IaY3APW0e3AUt8l1lkRUtm8D25+wSjocWp1YTkEE2APFaZ5H2fviN3\nE62l+y8UURq1hk1HrjAKLFU57r964PrTNS1pqSr7WbI9xa5UTFW+pSo9x2HiVcSwMfQyuYLfiwWs\nJteXkqadeXznscQ+2ew/PXpeTffbUigUZwazYO6/FC2KKAKJdHSQ3jKlWJXcKtKnKap894P0Bpvj\n/jN1MyECPTduQ8hUTu0oR7Im1b0q7/3q3/LYXknMZCxVUSekc+UPMnuOpIK5NTeyULXzNn3r8W9N\nu00+bVzz4POpKTuTCg9J91/ZTGYherSe+kdG173YKmc08OzCtGI9KRokEdQoARpazXeBah2Tif2i\nYHzHS7oJvXxRFd+nsYUvuhSam7RgAZ5jsrBrPp5mB8dKrnc9EsU6R05UUsfPJwyIH6+0SDBp4f6L\nNslLAAn2Mwndf3XGTtX43HefjCZAbgTxXd2dZsKqZvT4gfZLexYnXiKu3bws9/xpUWXLU1MZju/O\nzrkWLnG7tcQzR4ueH5ErVbcxF+yKBJ+8rT2ylMaBlQx2zMttn0KhOLM480VVOvhzOvdf6nM03Ykr\nxaroORaN0xRVHcUCi+fFWTmelnX/FU0z2V6nEDQqfrCfqiQtG1PVRuatv7BkOw9NSNaClLUtGlza\nCNztKKeWa7ErrO2586BlgmXy+O0fJBqsqm5urJnjxtPUdKREleN6p2GpiuPINLPhu/6mEesJ9598\n7et+O7yqny6fHlhDS5HdcONzSG6hsO0R0X2azYiU45Hk4xeNYjAHZboQq5frXk4cX0LvPhGvDubq\nc7Tmc1/K7lJ5iqDx+gRewbeIabqXsYp1BSF4Jv7voe42+NbtO7n3qSN88ftP+8tsF2NgP41z/hWt\nI34RCGP5lnQvTtw+5y4bym2inLzwzR/vYPfhOGvPd//puc8Dz4vdlEhTDMmXMyyIWlp7H4VhC3Mo\nZcV1NbxKL/aBVWreP4VilnDGi6rMkNBELISkK6prOZaqXFF1muZ5QzNYvmBOvLeWtVQVjeRg7dmF\nuA0BU7V4+5GxCh/4zJ1UFt3T8tx+vSJ5oMp5YLsGH7tpMwUjeb0m0pYHzZXmjssOtJ6rUd+xEXcy\nndbd7iCRf109V8u4aqO/PS3X/We7cqB6R2JdrWG3nf2nGX61cMd1wLDx7MK0Yj0hdHNElT3pB9br\nHUlLYChyGrYb34MpUeW2slSlp87R05YoL3KjoTtJEaU1jylKW7wASuvuyyxzqBN+L0UzeY00adJw\n+fr86QN/GW+TY6nq6gpc0kG7K3Yl+h2EltuG7VJcsRUAoy92s4XJJAPlecj3YNHIr1EWWn2fPGbx\n7zvvJnG/6Q10w6W0NtvvkbGp2FJFytocfCdhFqjelS0H4W+rpqVRKGYbZ7yoygzK01gUgMR4r0fz\niwX76V7ugDKdpSo96BqanpwqQ/MHaVlUlQqFpAgMyhvonRNonX5W1WQ1HpiePXAyEfzbjEJBSw5U\nkadIdv/p9HYWeM8bzknsO15LuSg0r7X7zzFxji9s77q3IlMaI8y6GiHqQFRpW891//3DbRa7DvvW\nlJ5CMuNwYqpxGu4/3+V5ql71RbgzvfsvUTYiR1TVpoIYr2IySy7f/ZcUVftGZCGm+UJILqMQrcpa\nqio1h607gpIdRvbe2XNkgvGpnESCNi2znnTOYlQ4M4gfk2pm1Ro2W3f54udETUrO0L3MueygTIjh\n+ULoiaNPs6/7PyltuING6Th/9uDNfH3Xl1q2y9QKiWtY1Au524W/x7967Au+SEvEdjk4naPondn6\nZifnPhhZxZKlU4iOIZdgyEWJKoVi1jELRFWSad1/KeuHnheonmOp0nKtVxKpB6ShG5lJf7+x7TuM\nTB2NPpfNpAXEC0RVYfFOyuvvBoK3Xd0GPE5O1jODch5dHXoqLizf/afrWma6l/S8e9Nm/3kpdxRQ\nWncPxuDPGLAutQ+gtOoRzEU7o7YAfOStF+RaqsZOVTlVq2LqZiam6vGdR7nv6cNtnTqcLPhUzb8W\nXhvuv+ONkTiTUsKb9Oe4qVaCayfdR1W7yo/3/RSAhu3Fwj5lqfIbJR9U+n6l71nT8i1M4bXsOP92\nv2xIfCAATkzEpUK08ikoVHPdf02Jyhg0t07uODDGp7/xGEdSddfkbL+QRlAq/6ePjUbLpgqH0ctT\nTA48zO7xvRyoJJM7Erh65vsqGPmiKpO1KQtP3W7qljN6TkSWsmRcJITXdbr5EKdNqlEoFGccZ/yv\nOjOzezvZfzmWqmndfy3S6QE8JyWqNAM9NanrXQfvT3wuFwr57r+ocQ5asULH5v+gMPwM37htR1ui\nasOquRjyqWULSIhjomlaZq6+KTtZ3T0UGL/1V3fx7MFUkVIkC58c/N99smVNp+QJ4lT6xHGl66n3\nHktsu3xBH7ljXRAPV9ALlHLcPbVGm3P/GTaVBQ/wxLGn/M92oS2rQvncuxLtBHCOz/f/dcFzdDTd\noeE0OF49wb2HHoq2a9geuJIlsZWI8yRLZNqilGfJbNb2nDpg5Q0/peP8209LVEW1oQyNZu7c0MqZ\nKL0QtiF1robni6r9R/KC4Kdvl+aZOK4XxRJqaJhN5kra03kbO8Z2xfuaUvsMm4LRxiMyXVNMi0VV\nudjKDX7GP34VCkWKM/5X/eub35Fc4E0TU+VvFH2OLDVSoHre2/5pW6o0PSv4UpQLxaQITIkqzaxF\nbkBzgV8gtB1R1dtlMH9uKbtCdv/ZBUwjG5tUsdNT5rgcPj7F8fEaJ07lnDts/3Qp+KeLm3Sdyv/6\n1oO8bEFfEJuaiZlx93iYQ3vbOrXdux+37wD/ujuYo9Exk+UopsXDneqh8uDVJH5irgG6y2ce+Swf\nv/sTTNqxaPCtGkF6fZ6lSj56vYxWquJn/iWve56YTQv+piSsNKcRQxgErWudJ+i46Ee5U+VExUpT\nLti8mKqw9lqedTCMTWyJYwZxaP41LOhmrmUToGoe5f8+/Ndxe6Tfl6fZFNopOiNbqrz43mzYLr09\nZ/wjVqFQnAZn/C9+Vf/K5IK23H8xUfaf7MbKGxRy4lESpAYuXTcoNnE5hHQUk7E6np2yrhTSsS5e\n/NBvlGgcXJ57XM1wk26NKABaWmQX6CiZGZdN3UsJp3QgdIacgOnMJqef2SQH8Wpy/JAHuqbn1/XR\nPDTdwaDAWC1ZVFUrVdG7sxNs5547XUuqTUuV3A7PNpPCEL9PWqnC7nFf3I1V4zaOnapj6rLVtIWo\nqnb5wsWMg8Qj8u7TNtsuB5ZPV/wzsV9wvarzH2u+TVRmICWKNDcScBlLbc594xamnyPUcw0/YzK4\nNAW90HZ2nT+7gE+1dJh93bdPv1Pa/Sf9Frq7zvhHrEKhOA1m3S/+vJX5qdMRGklXVRSoHrgKDAet\nVMnuN42lKp3JY2g6A73ZqVQGWRH9XTILicKB6UFFK9QSb/1asYJW8F0jXQe34FXzp3/RjXT5gKz7\nz6SEaegZUZW2MhhzjkqxQjlCJiyA2GoQbil0vdS/AbJIDawvmu6AZwZbZ9tiDhz0t3UNzhs8N7HO\nmDOa2b5Fg1NtmT5QPSasG5WfcSlbkkYqcXydbbsU9FCEtbZUuRX/ey9vuBNj3qHEusLinbnnzSUt\nhM0WUx21IrBUuaWsezh9rkzdNS22trUjqpqRCPdzjMAi5u9v6EaiFle71ArHpt8IcKV7w/U8NN3D\nmL8bgK5uVSpBoXgpMetE1fBgX8v1Td1/YaB6eTK3+Kc2naUqZZUwNCM3OHYeZ0V/Fw0zmSHYSFqq\nMqKqVEULrFedZmcU2J5pq+ZhyxMsh5UIpEGqZPiB3Bm3SI6VLspyCq5L5YFrsEeW+ItCkdDCUtUy\neSAn3AtICIHIOmfa6K5/TfMyEaNYLtdgUfcC1hRf1vy8rUgX0LSTsW+tics+ZEiJm8OTI9JuGkVT\nslS1cv8FYlozbQpLt0/fojbdf+HUM/6H9t1/0/42IBJpcjYr+HPvFYaDWa+ei6iqxS8wrmP4czcG\n+xua8bzWgQrv76mqjWP42bPFs57BGNxLqdxqT4VCMduYdaLK1KcJgkh5VpIuFykoOs10lqqcQPW8\n4FgzniOEomkm2pt2/2nFWsKdoxWqkejp7+iJi4WmcKhzqiGXRshm/3Uafh2ndKB6XjxMvCwWDJFV\nIXSVtbBsPNd6PJrhgOagGQ20QFQ1LVpJ/F2E2z5nHHParNKI4BKbOQHO6Xsk8R1pUJCzC1qIuGie\nyjYp6vk1mvSeE8kFpiR42k00ADAaLb9/3TNB8ygMP82TU8lkjbo2hd7tW7gylqrTsC55tbgumecY\n3PHowbh5P6Olqu1zBwkGH/jMHXjSc6K4/CkM8zSuo0KhOOOZdaKqMI2oSj9aS4XgQR4MYsmU8xhz\n4FBmmSdla6WtELquU8ipjaO78QBXNJKiqstMugsXDBkp918Nzazj2SZLh3pZOT9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vAAAF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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ae051b828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/+8i6nj4EXI6lwDzgIYfbuWS2LDoKS4E8ApDZKsa+HgAvx7pO99vHmoCTbJkylpqVWBai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\nEEKY4P8BmpUezl5RRRUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ae047f3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gumpy.plot.reconstruct_without_approx(\n",
    "    [details_c3_c2[4], details_c4_c2[4]], \n",
    "    ['C3-c1', 'C4-c1'], level=6)\n",
    "\n",
    "gumpy.plot.reconstruct_without_approx(\n",
    "    [details_c3_c1[5], details_c4_c1[5]], \n",
    "    ['C3-c1', 'C4-c1'], level=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([array([-0.04379641,  0.17916636, -0.15634663, ...,  0.05339261,\n",
       "         -0.05486782,  0.01305731]),\n",
       "  array([-0.01783179,  0.0415965 , -0.07318729, ...,  0.03480512,\n",
       "         -0.01006542,  0.00087816])],\n",
       " <matplotlib.figure.Figure at 0x7f5ae052b710>)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KvReTafwOx0olezFeu0CIh0kQBEE40tjjWAj3XGCz1joNrMB4S57ACKgfYDxPXRiPyoft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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ae052b710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gumpy.plot.reconstruct_with_approx(\n",
    "    [details_c3_c1[5], details_c4_c1[5]],\n",
    "    ['C3', 'C4'], wavelet=wavelet)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Welch's Power Spectral Density estimate\n",
    "Estimating the power spectral density according to Welch's method is =imilar to the power reconstruction shown above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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aUkvQ7yaVKcw4WUmy8pCC24RMMcORseMNXToSyQsVq2lDnYVrCu5YZn5u5cls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\nJ+kbjHNLg+5Eljt537bOquOKovDOV13Dn3/pIF/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IWCbBZMoIZC85XDArDmOuE6xF3OpU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\nQckX3FRCBFcQwojgNqrbXjBlmRpvDr8AmEgNTnAnksZ5rVbWgolCgw4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criBsjFwVwjWN\nzeEOaugFgNs2T/nKchGPreVvoRk+rtYaOzaHOyhiUjQlCBsiV4VwTROeBwyDEVwwlcrW4fZSoQyt\n4x2DKuXrtJgo1lE0JS8tgtCOXBXCNU37ZKlB5HABxjMJ8qUa9UajpwplaF1gEDjc5PV5ycVd87xs\nSPl6fWMhCP1wfV79wq4iE3K5g2gLgvA85RpnL68BcGBma/cdzFOuNYL2oOtViDrbguSlRRDakatC\nuOYJC+7AHG62OU/5mdNLZFJxDs1tbYdveJ7y9Z/D9QVXiqYEoStyVQjXPLZSGZrLDPrFOtwzF9e4\ntFjk1kOTuO7WhkOEl9BXduBox0FiQ8q1egPHaVYtC4LQ5Pq8+oVdRTZhHG4mnibW55o5i3W4j+tL\nAKgj01u+Dyuu5Vo9KJq63h0uGGff7+QqQbgeEcEVrnmsw83FB5O/habD/dZJM1BDHdlaDy5Eh5R3\n2qSpQRFzmy8lEk4WhGjkyhCueQLBTQ4mfwumShlMiDSdjHFk39byt0CwbD4cUr5eHW485HBFcAUh\nGrkyhGseO/xiUD240AwpA9x6eKrFwW0WOwayUqtTrprcZliYrifs4AsQwRWEbsiVIVzz2OEXufgA\nHa4fUgZQWxzpaEm2OdxU4vrNbcbdcA5XXlYEIQq5MoRrHluZPKgeXDDzlC29FExBM1/79e9d5spy\n6brN30Jr0ZQ4XEGIRpYXCNc8QQ53gIIbj7nk0nFqDY+j+7eevwXIpc3l9d0XFwG45+jcwM6304i3\nhJSv3zcWgtAPIrjCNc/xPTdzz967uGffXQO937f84M24jtNT/hbgpoOT/OQbjpNJxbnhwAR7JlID\nPd9OItx3Kw5XEKIRwRWueTLxDO+64+0Dv98H75rv6/au4/BAn/dxrRAumpIcriBEI1eGIAh9I21B\ngrAxcmUIgtA3MvhCEDZGrgxBEPqm1eFK0ZQgRCGCKwhC34QdruRwBSEauTIEQegbyeEKwsbIlSEI\nQt/IaEdB2Bi5MgRB6Ju49OEKwobIlSEIQt+078MVBKETEVxBEPpG2oIEYWPkyhAEoW+kaEoQNkau\nDEEQ+qbF4cbkZUUQotiRs5SVUieA3wROAp/SWn9hxEcSBGEdwg7X7gEWBKGVnXpl3AtcAOrAd0Z8\nFkEQNqBlPZ84XEGIZEc4XKXU+4DX+h9+Bfgs8P8A+4D/DfjAiI4mCMImcF0HB/CAREKqlAUhih0h\nuFrrjwEfsx8rpd4GnAcW2SFnFARhfWIxl1q9IQ5XELowdDFTSr0S+GWt9UNKKRf4BHAXUAZ+Smv9\nXMTNXgQ+DlSB/2PYZxQEoX9iMYdaXXK4gtCNoQquUuoDwDuAvP+pHwXSWuv7lVL3Ab8OvKn9dlrr\nLwNfHubZBEEYLHHXoYzkcAWhG8O+Mp4H3hz6+NXA5wG01o8Brxjy4wuCsE3YwinJ4QpCNEMVXK31\nZzBhYcsEsBz6uK6UkhytIFwH2PGO4nAFIZrtvjJWgPHw42uta9t8BkEQhkDcH34hOVxBiGa7r4y/\nBX4YwM/hfmubH18QhCERi5nWoFhoc5AgCE22O5z7WeB1SqkvAw7wk9v8+IIgDImY65KIuziOCK4g\nROF4njfqM/TN5cur1/6TEIRrnL964iwLqyXe8tDNoz6KsEnm5sbl3dE2IoIrCIKwSxHB3V6kukEQ\nBEEQtgERXEEQBEHYBkRwBUEQBGEbEMEVBEEQhG1ABFcQBEEQtgERXEEQBEHYBkRwBUEQBGEbEMEV\nBEEQhG3guhh8IQiCIAg7HXG4giAIgrANiOAKgiAIwjYggisIgiAI24AIriAIgiBsAyK4giAIgrAN\niOAKgiAIwjYggisIgiAI20B81AcYFUopF/gEcBdQBn5Ka/3caE9lUEolgN8HjgEp4F9prf98pIdq\nQym1F3gCeJ3W+plRn8eilPog8EYgCXxCa/17Iz4SEPxOP4X5ndaBn94JPzel1CuBX9ZaP6SUuhn4\nJOAB3wZ+Rmvd2CFnOwF8HPOzKwM/obW+uBPOFvrc24D/RWt9/6jO5Z8j/HPbC/wOMA3EMD+350d5\nvt3Mbna4Pwqk/YvjnwG/PuLzhHkEuKq1fgB4A/CvR3yeFnzx+DdAcdRnCaOUegh4FfADwH8HHB7p\ngVr5YSCutX4V8C+B/3PE50Ep9QHgd4G0/6nfAP6F/3fnAG/aQWf7vzBi9hDwp8A/HdHRos6G/4bg\nf8L83EZGxNl+Bfi01vpB4F8Ax0d1NmF3C+6rgc8DaK0fA14x2uO08MfAz4c+ro3qIF34NeC3gXOj\nPkgbDwPfAj4L/Cfgc6M9TgvPAnE/sjIBVEd8HoDngTeHPr4H+KL/7/8XeO22n6hJ+9n+gdb6G/6/\n40Bp+48U0HI2pdQM8EvA+0Z2oibtP7cfAA4ppf4r8Hbg0VEcSjDsZsGdAJZDH9eVUjsixK61XtNa\nryqlxoE/wbwz3REopd4JXNZa/+WozxLBLOaN01uA9wCfVkqN1HGEWMOEk5/BhPh+c6SnAbTWn6FV\n+B2ttZ31ugpMbv+pDO1n01qfB1BKvQr4WeCjIzpay9mUUjHg94D3Y35mIyXid3oMWNRavxY4zQgj\nA8LuFtwVYDz0sau13jFOUil1GPgC8O+01n806vOEeBfwOqXUo8AJ4N8qpfaP9kgBV4G/1FpXtNYa\n44LmRnwmy/sxZ7sVUzfwKaVUeoPbbDfhfO04sDSqg0ShlHorJrLy32utL4/6PD73ALcAvwX8B+Bl\nSqmPjfZILVwFbP3Hf2JnRfJ2HTvC0Y2IvwV+BPiPSqn7MKHIHYFSah/wX4Cf1Vr/1ajPE8bPBQHg\ni+57tNYXRneiFr4E/GOl1G8AB4Ac5gVnJ7BI03ksAAlMEctO4utKqYe01o9iage+MOLzBCilHgH+\nEfCQ1nph1OexaK2/BtwOoJQ6BvwHrfVOCC1bvoSpH/h3wIPAd0Z7nN3Nbhbcz2Kc2pcxhQ4/OeLz\nhPkQpqrw55VSNpf7Bq31jipS2mlorT+nlHoQ+BomevMzWuv6iI9l+Sjw+0qpv8FUUH9Ia50f8Zna\n+Tngd5RSSeBpTDpj5Phh29/EhET/VCkF8EWt9YdHerBrg58Dflcp9T9jUmhvG/F5djWynk8QBEEQ\ntoHdnMMVBEEQhG1DBFcQBEEQtgERXEEQBEHYBkRwBUEQBGEbEMEVBEEQhG1gN7cFCdcxSqnfBx4C\n/rnW+t+P+Dh94fc7H8LM/L4DQGv9kdDX34npT31nl9t/GtNX+0+01p8c6mEFQeiKOFzheuWdwPFr\nXWxD/JTWuqe+WK3122lOGxIEYUSIwxWuO5RSf44ZZvI1pdS7gX8LXMFsN/p7wK9i3G8M+KTW+qP+\nzOVfB/4+ZinDJeA/Y4a9P6q1Pubf90fAOEyl1N/DbP5JAC9gVu5dVUq9iJns8zBm2tVPaK2f8DfK\n/Bsgi5k29XbgF4H/prX+Hf/+HwX+qdb6qz087yRm6IflBsxo0J/d6n0JgjB4xOEK1x1a6zf6/z+B\nEU4FPKK1fh3w0/7X7gbuBd6klHoAs/DgHsyYvrdixuB1RSk1h9kQ87DW+vuAvwR+OfQtV7XW92Jm\n/37I/9yngV/QWr8cM3f3H2P2Hr/Dv8+jwNwmxPY9Sqlv2P8woo8/Q/qE/7z/EXAB+MgG9yUIwjYh\nDlfYDVzSWr/o//u1wAml1Gv8j8eAl2OE9jNa6ypw0XfJ6/FK4AjwBX/UYAzjWi2f9///beDNSqlZ\n4IDW+nMAWuvfAvCd9bw/h/cdGDe+Eb8dlcMNfXwQ+CPgx7TWVzZxf4IgbAMiuMJuIDyDOgZ8QGv9\npwC+EK4B/6rtNnbRgEfrUvGE/7UY8CXrpv3NP2Oh7yu13b7q/5vQ989rrU8qpT4F/I8YZ/36Hp9j\n+H7/DPiw1vrr/dyXIAiDRULKwm7jr4GfVkollFJjmG0q92FCwv9AKZVSSk1iNqyAWVG3Ryk1p5RK\nYXLAAF8F7ldK3ep//PPAr3V7UK31MnBWKWUF9R34oWDgk5j9vae11uf6fH6/h8kJ/2Gf9yMIwoAR\nhyvsNn4bs7/065i//z/w19GhlLoHeBKzSu8CGKFUSv0K8HfAGfyiJK31BaXUuzDrHWPAWeCRDR77\nEeC3/Pu7gp+71VqfUUqdxghvz/jL2d8GPK6U+jrGWX/Hr1IWBGHEyLYgQYhAKfVJTHXyJ4f8OA5m\nd+8XgTu01uWI73kU+Ih9Y9Dj43ySbXg+giB0R0LKgjBa/gfgm8AHo8Q2xO8qpX6slwfwB1+8sZfb\nCoIwOMThCoIgCMI2IA5XEARBELYBEVxBEARB2AZEcAVBEARhGxDBFQRBEIRtQARXEARBELaB/x8z\nVdqCJ3igbwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ade993d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CcOO43hHuIPDusv9/CPg2gCGk91zn8wsEgsvk/JguZP1dQew2mTu3NpMrlCqcnK6G0Zg+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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ae50af908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# the function gumpy.plot.welch_psd returns the power densities as \n",
    "# well as a handle to the figure. You can also pass a figure in if you \n",
    "# wish to modify the plot\n",
    "fig = plt.figure()\n",
    "plt.title('Customized plot')\n",
    "ps, fig = gumpy.plot.welch_psd(\n",
    "    [details_c3_c1[4], details_c3_c2[4]],\n",
    "    ['C3 - c1', 'C4 - c1'],\n",
    "    grazb_data.sampling_freq, fig=fig)\n",
    "\n",
    "ps, fig = gumpy.plot.welch_psd(\n",
    "    [details_c4_c1[4], details_c4_c2[4]],\n",
    "    ['C3 - c1', 'C4 - c1'],\n",
    "    grazb_data.sampling_freq)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Alpha and Beta sub-bands\n",
    "Using gumpys functions you can quickly define feature extractors. The following examples will demonstrate how you can use the predefined filters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def alpha_subBP_features(data):\n",
    "    # filter data in sub-bands by specification of low- and high-cut frequencies\n",
    "    alpha1 = gumpy.signal.butter_bandpass(data, 8.5, 11.5, order=6)\n",
    "    alpha2 = gumpy.signal.butter_bandpass(data, 9.0, 12.5, order=6)\n",
    "    alpha3 = gumpy.signal.butter_bandpass(data, 9.5, 11.5, order=6)\n",
    "    alpha4 = gumpy.signal.butter_bandpass(data, 8.0, 10.5, order=6)\n",
    "\n",
    "    # return a list of sub-bands\n",
    "    return [alpha1, alpha2, alpha3, alpha4]\n",
    "\n",
    "alpha_bands = np.array(alpha_subBP_features(grazb_data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def beta_subBP_features(data):\n",
    "    beta1 = gumpy.signal.butter_bandpass(data, 14.0, 30.0, order=6)\n",
    "    beta2 = gumpy.signal.butter_bandpass(data, 16.0, 17.0, order=6)\n",
    "    beta3 = gumpy.signal.butter_bandpass(data, 17.0, 18.0, order=6)\n",
    "    beta4 = gumpy.signal.butter_bandpass(data, 18.0, 19.0, order=6)\n",
    "    return [beta1, beta2, beta3, beta4]\n",
    "\n",
    "beta_bands = np.array(beta_subBP_features(grazb_data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature extraction using sub-bands\n",
    "The following examples show how the sub-bands can be used to extract features. This also shows how the fields of the dataset can be accessed, and how to write methods specific to your data using a mix of gumpy's and numpy's functions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Method 1: logarithmic sub-band power"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def powermean(data, trial, fs, w):\n",
    "    return np.power(data[trial+fs*4+w[0]: trial+fs*4+w[1],0],2).mean(), \\\n",
    "           np.power(data[trial+fs*4+w[0]: trial+fs*4+w[1],1],2).mean(), \\\n",
    "           np.power(data[trial+fs*4+w[0]: trial+fs*4+w[1],2],2).mean()\n",
    "\n",
    "def log_subBP_feature_extraction(alpha, beta, trials, fs, w):\n",
    "    # number of features combined for all trials\n",
    "    n_features = 15\n",
    "    # initialize the feature matrix\n",
    "    X = np.zeros((len(trials), n_features))\n",
    "    \n",
    "    # Extract features\n",
    "    for t, trial in enumerate(trials):\n",
    "        power_c31, power_c41, power_cz1 = powermean(alpha[0], trial, fs, w)\n",
    "        power_c32, power_c42, power_cz2 = powermean(alpha[1], trial, fs, w)\n",
    "        power_c33, power_c43, power_cz3 = powermean(alpha[2], trial, fs, w)\n",
    "        power_c34, power_c44, power_cz4 = powermean(alpha[3], trial, fs, w)\n",
    "        power_c31_b, power_c41_b, power_cz1_b = powermean(beta[0], trial, fs, w)\n",
    "        \n",
    "        X[t, :] = np.array(\n",
    "            [np.log(power_c31), np.log(power_c41), np.log(power_cz1),\n",
    "             np.log(power_c32), np.log(power_c42), np.log(power_cz2),\n",
    "             np.log(power_c33), np.log(power_c43), np.log(power_cz3), \n",
    "             np.log(power_c34), np.log(power_c44), np.log(power_cz4),\n",
    "             np.log(power_c31_b), np.log(power_c41_b), np.log(power_cz1_b)])\n",
    "\n",
    "    return X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(324, 30)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w1 = [0,125]\n",
    "w2 = [125,250]\n",
    "\n",
    "features1 = log_subBP_feature_extraction(\n",
    "    alpha_bands, beta_bands, \n",
    "    grazb_data.trials, grazb_data.sampling_freq,\n",
    "    w1)\n",
    "\n",
    "features2 = log_subBP_feature_extraction(\n",
    "    alpha_bands, beta_bands, \n",
    "    grazb_data.trials, grazb_data.sampling_freq,\n",
    "    w2)                                          \n",
    "\n",
    "# concatenate the features and normalize the data\n",
    "features = np.concatenate((features1.T, features2.T)).T\n",
    "features -= np.mean(features)\n",
    "features = gumpy.signal.normalize(features, 'min_max')\n",
    "\n",
    "# print shape to quickly check if everything is as expected\n",
    "features.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Method 2: DWT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def dwt_features(data, trials, level, sampling_freq, w, n, wavelet): \n",
    "    import pywt\n",
    "    \n",
    "    # number of features per trial\n",
    "    n_features = 9 \n",
    "    # allocate memory to store the features\n",
    "    X = np.zeros((len(trials), n_features))\n",
    "\n",
    "    # Extract Features\n",
    "    for t, trial in enumerate(trials):\n",
    "        signals = data[trial + fs*4 + (w[0]) : trial + fs*4 + (w[1])]\n",
    "        coeffs_c3 = pywt.wavedec(data = signals[:,0], wavelet=wavelet, level=level)\n",
    "        coeffs_c4 = pywt.wavedec(data = signals[:,1], wavelet=wavelet, level=level)\n",
    "        coeffs_cz = pywt.wavedec(data = signals[:,2], wavelet=wavelet, level=level)\n",
    "\n",
    "        X[t, :] = np.array([\n",
    "            np.std(coeffs_c3[n]), np.mean(coeffs_c3[n]**2),  \n",
    "            np.std(coeffs_c4[n]), np.mean(coeffs_c4[n]**2),\n",
    "            np.std(coeffs_cz[n]), np.mean(coeffs_cz[n]**2), \n",
    "            np.mean(coeffs_c3[n]),\n",
    "            np.mean(coeffs_c4[n]), \n",
    "            np.mean(coeffs_cz[n])])\n",
    "        \n",
    "    return X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# We'll work with the data that was postprocessed using a butter bandpass\n",
    "# filter further above\n",
    "\n",
    "# to see it work, enable here. We'll use the log-power features further\n",
    "# below, though\n",
    "if False:\n",
    "    w = [0, 256]\n",
    "    \n",
    "    # extract the features\n",
    "    trials = grazb_data.trials\n",
    "    fs = grazb_data.sampling_freq\n",
    "    features1= np.array(dwt_features(btr_data, trials, 5, fs, w, 3, \"db4\"))\n",
    "    features2= np.array(dwt_features(btr_data, trials, 5, fs, w, 4, \"db4\"))\n",
    "\n",
    "    # concat the features and normalize\n",
    "    features = np.concatenate((features1.T, features2.T)).T\n",
    "    features -= np.mean(features)\n",
    "    features = gumpy.signal.normalize(features, 'min_max')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sequential Feature Selection Algorithm\n",
    "``gumpy`` provides a generic function with which you can select features. For a list of the implemented selectors please have a look at the function documentation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "[Parallel(n_jobs=-1)]: Done  30 out of  30 | elapsed:    0.3s finished\n",
      "\n",
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     ]
    },
    {
     "data": {
      "image/png": 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GnH7WSvbcN899d1kTiakOlZaIs1T13uTO4BhYICKfGWabR4DDgVuTPoCny1eK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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ae02453c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_idx, cv_scores, algorithm = gumpy.features.sequential_feature_selector(features, labels, 'LDA', (6, 12), 10, 'SFFS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selection Algorithm:  Sequential Forward Floating Selection (SFFS)\n",
      "Average Score:        71.6920210166\n",
      "Feature Index:        (4, 6, 8, 11, 12, 13, 14, 23, 26, 28, 29)\n"
     ]
    }
   ],
   "source": [
    "# let's see some information about the results\n",
    "print('Selection Algorithm: ', algorithm)\n",
    "print('Average Score:       ', cv_scores * 100)\n",
    "print('Feature Index:       ', feature_idx)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA \n",
    "``gumpy`` provides a wrapper around sklearn to reduce the dimensionality via PCA in a straightfoward manner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "PCA = gumpy.features.PCA_dim_red(features, 0.95)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Splitting data for training and classification\n",
    "Now that we extracted features (and reduced the dimensionality), we can split the data for \n",
    "test and training purposes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(259, 30)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_size = 0.2\n",
    "\n",
    "# gumpy exposes several methods to split a dataset, as shown in the examples:\n",
    "if 1: \n",
    "    split_features = np.array(gumpy.split.normal(features, labels,test_size))\n",
    "if 0: \n",
    "    n_splits=5\n",
    "    split_features = np.array(gumpy.split.time_series_split(features, labels, n_splits)) \n",
    "if 0: \n",
    "    split_features = np.array(gumpy.split.normal(PCA, labels, test_size))\n",
    "\n",
    "# the functions return a list with the data according to the following example\n",
    "X_train = split_features[0]\n",
    "X_test = split_features[1]\n",
    "Y_train = split_features[2]\n",
    "Y_test = split_features[3]\n",
    "\n",
    "X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting features\n",
    "``gumpy`` wraps 3D plotting of features into a single line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KzSsUuH58nJuy2WrPewy0OycKd7+L1PcfgMlJ/KXLsLe/iftSFof14H3vNBRv\nLdhsKRNvJ1F4e1lbQFH9/b1tzZK6jVa+C3v2DPIXf/HpyravvLKT//Jf/jvXXXd923XPOdJth04j\n3XA+VGgcXv/ld2MfSgX64bBA1mofM5GYhWkEIaBQaBXZhoQen7hM0ygXyfyuj2APUa2aB4+jSiny\n+UKkyyqY5BDmBquOXFVC7gSqr4/SW95a87chIXjQsginFD1j6Cz1/DKRVL8Q7cABUt/+JiKf5+SC\nBZz80IfQ5s8HoCQFT5s6v9YkKGjWkZZFMaJU5XPIej4nC0UU8J1Mmj2mjqFrfNvI8nu9ggEhGPEV\nfw082N9DQQg27dvPwv37eV4pbnv+BQof+C0wzQZvXiGPHgXfw79gRZAuaEOSamCAwnvvrfxuAwc1\nWWl00BC8qmszIt1mCGVtruuSyVgMD48G+4rcoENZ2yuvvMIf//EfV3wXLrxwHZdeejkDA60HRLZD\nK9+FDRtyfPazfwPAI488zMKFi2IRLpyjpNuKmOISYnRUulKKycm4xuHxibFqTi4olbxYHV6dEHpY\nsEmnzTZk29lxhwhNek4X2baCUjSc5BDHLtJx3I5bu4/XNZroQnBSE+CFkWBwblg/+B7CdcE00Scn\n2fL9B3jx3vdXXtd+r9PPsduLNl9NW5wUgn6leHMxeL+nhGCHhJTr4eBhA/c7DrfbLt/t72FE1zGk\npOD5HJCCZekUyvdJTU2iP/1zCjffUmsUrhSpr92Htns3AvBWraJwz/sQptERSerUEociSLNUPoMu\n5pvrpwDX36ABFi1axr/9t/83Bw4cYP/+AzzwwHc4ceI47373b85q3618F0IUCgU+97n/xWc/+7ex\n1z0nSbcV2hFLo6iwtzfTUbqgXQogOgkinKzbaTTWClHz8+CGUZj9Y3cZ4YRYIJZ941yjVftvWLhL\npy0Mw0BK0VBJ0YgQVnsehlL45ZPHQ3Fhg/cuIjPE+pVi2WSBZwnyuxnf55oWqa9mj/HzlOKj+SJu\neZ3wzFLUnpGVvyvFmILdvk/e85j0PBSCguux7eBBAHSl6O/vqbkheS+9hDx0ED8VtI5rx45hvPAc\n4vobOiJJCdxasnnQMnEELPQVb7SjLmlza54jhGDt2nWsW7cBKWfSaNwY7XwXAO6//9u88Y3bO4qq\nz0PSbRwp1nrZ1huHd8d/oZZsq1aRpqnHXj/upInwhtHZpInma9e3Amez6Y7ytmdaHxlGQKFFYipl\nYVmBYU+OKUbGAAAgAElEQVSYpmjWceY4Lr2ux7uKRR43THzgMsdltTf9M/VWr0bfvy+o5rsul61a\niSqWKAFbXK9NB13r76n+YlygFDnX54AmkUJgKMXVtosP7JKCIxH7vI1jo7z3mWfYMHwKG8iv24iK\nPJIbhoZRKGKYBlIPzkff8zF0iV/OCXdiE3mF67HJLZAXgnlK1ZjZdNc858wNpWzluxDiwQe/z3/6\nT/9fR+ue96RbNXFp7mXbTDbWfB+10XRAhiZC1JJts+07Wbt2fTEtjTBbtUO0+Fb7+Zw5XWQ3CTyq\nIBgXsEfTWAKslbJGQaDrGgs9j61h0U5puGVtbvR4inf9OuaPf4wYG8FfsRL3mmvZGrOQ0+nbEsC7\niyVe0DWKQnCx69Kn4KQQ9AAX+j6nPJ/FKN6wei2r1+zHuWAl9tZLUMuWVdYJb0jFC9fhaQZyKiAS\nkUrhXryVlAzkbY1sIsP8eSMSzQCZBn+fjbJn+lpnzuymle8CwOTkJI7jsGTJ0o7WPSdJt11OV0ox\nbX5Xqwpn58bkqqLDrI88m7yC+Hfh6rbNIudGxxLvuKufW3js0FxW1s2LJy46feqIiyNC8JVMCl8I\nPKW4wXG4aao2x17b7prCMLTKsfT19VSiYudNb4oXyRUKWA/+ADE+gb9yJdxxR8efpwAuj567nkcm\nn0fr72EVsPzIEeTh1+g7PsRzl1/B4JIlZFDcWnKYVkYzTfIf/m3Mn/8UFDhXXY3STUTJxnUDk3Ah\nREVFUvt0oGqaPZoVMLvdyHAmGyPa+S4cPnyIZZGbW1yIVm9oaGjirGwDkbL56HHLMkinLRzHo1gs\nxSoApdOBUXf9XKtW25umjlIqVgErk7Fw3el5yGYYGOjBdb2WZBuipydQXcSRzQQTe30MQ0PK6VFz\nFH192Y6Ki2Heera562w2jRCCycl8+41bIEwvhMMRv5oyORR5NFRK8YmpAhLIA7/UJPN9xYK660EI\nweLF8zk2PoVmaAzogZIgJKGokqL+O0j/w9+hHT8OQqA8D7ntJuSKFUydOIm7+WJIpzt6T+LwYdLf\n/BpyfILHr76Sh6+9DvHssyx//RhvffhH7F2/nkf/w3/EMwwWex4fjDmENM5nLqWs5MyjN6d6CZfn\n+QwM9DE0dKqj9zabY4Mw2DK66qU7Gyxa1Ns0cjgnI91GsCyTVMqonPj5fKGDqKKzdlopBZ7nMTkZ\nzxuhU7UD0LIBZCZrV6fUxh1NFE9epmlB6iPsjw8uRK9u3Pbpne/VCPWfiap70lDlX48LwT9lUhTL\nL7ilZHNtXb7/W8CPNYnyFbl8gbuLNromGTZ0HrNMlKlzlUhzhR5x5HIc9KET+OWpB0JK9G99E7F4\nCSlf4T/5JIUPfxjV0xv7PaUeehBpO5BKsX33bq75xrco2CUWjo/z8tKl9Lx+jN6DBxnbsIGjUmLD\n9Gi34WfVPpoMgpLGAzdDMg7b5aUMJlrMvA28s2M713BOk2609z/qZdvXl+3oy2q3Wf30XiHoqFW3\n3SNzlbiCyFbXtdjjg9qlLsKmDyklnheMJeoGmUfXLRZL5RRFcEFGI6H6+V71keFcXVBXOQ6Hyoba\nrlJc5rhI4DHL4IgmOSo1CsArmmTJxBRryhH+ASn5BVXy2qdpvKBrbHY9/j6l4Xg+eD67UJRGS2wU\notoCPX8+WiEfFK3GJ1CnTsHKVQFxlooYP/0Z9m23NT1m/fnnMJ5/DqTEvuFGRCl6kxf0FKboHZ8A\nKdF9D89MUcgEPXEWxDYMn00aqb6Aqesa/f29jI1NNm0Dj5Mvrh6biEXWp8NL93ThHCXdwMvWshp7\n2c6kY6xRF1u9d0FoFBPMp5r9u6glrmrTRDod/w7fjBzr25lLJYdMxpr1MYddddF169GoSyiaKzQM\nnUwm8CKo19eeLhXEWs/n/fkie3WNeb7i4rIc7ISQ7NM0poRgREpA8r8zKe4q2lzpeuzRNQ4RTLFY\n4rpo5W2PSEleiAixCV7QdVaVbPSyb6/Yfjvp+7+DnJxE9Pdjrl2LFALLMpDSIt2fxRnom9ZhBaAd\n2E/qwR9WOsvUt7/FyQvXsnDvHqSmgevi3HU32v33o50aZv3Jk7z4rvcwuWwZllLcUbQ7oKDuFavC\n87ZRG/hM8sVSChzn/HEYg3OUdMMCx8TEVBPj8NlJwNqNSp/J+lFSb0a2kVfEXrs+0o0a9cze1yG6\nbnV6RbHodGw7qVTzFuCovtYs2yWaplEj6epGVLxUKZbW5bAX+D4CwWT5g8komJKSZ0yDPgVPmwav\nl0oUh45TODVCbnSUzUuWIRcuQpQ/+hEheEXXeE0Kjmga7yoUWa4UauVK8h/9HeSxY6hslr5HH0E7\ncADb9VCmQemiLWiFYiWtpOvpiq7Yf/YklIeCDgrBUWDnxZtZvmY1bz58BGPdhThXXs3UTTcH0bBh\n8Kbrb+CmfBGLQEsbF3Olq212DkTzxfUNL2EEGxLz2aYbnwnOSdKtd7SqR+ettMH27cy9q9vPbNpE\n1N+hVTtwJx4J4bbxSbETvXBwEYVDMANry2JXFQ31j6eZTLrsTVGqc+gKIqJTjsernsd812WJ7ba8\nCOMc5/WOww5XY8owUAiyPvSVb+TPGToWcNXOnezTdXwp+OATT7A0naHw/g+yvWTzmGWwV9dZ4Pus\n8RW2FPwoZfL+QgkKBTL/8HfIoSEQoG65FWfTJkqnxnC3bEH19eGW7Iam4ebCRaQ8j6JpMqRJMr6P\nv3E9Oxcuos92uMM0UJN59i9ZzEPveAclAes9jztKzvRv2POqrv8NcDqGUnaCVvniefN6AVV+utKn\nmac7jsv4+DiWlepqpNvKdwHgZz97ks9/PuhC27hxE5/4xL+J30nataM8i9ApKYbm4VLKWObenZK6\nlAGhG4be1nshWL+T9IiqyONaTZmorhv/uE3TwDD0mBMyuoVgH/UOXQBDusaXMml8QwfT4I1ZwW2a\nnObR2omr2ipfcXfBxlDwqqazQvlkFVxrO+zRNYSAdKlE7tQIoFg+PsGYgi+kLfJCsM510ZTCiTzJ\nlMq0Zz7+GHJ8HFJBy4T25OPYn/gkjqitsOsvvYD56GMIz8XZcgn29u24qy+kdM11vLbjRYZMixPb\nbmJk3nykUvjlfHl2Xh8/9BWu8lG+4hXPYwGCa8IWWaWw7v8OxiuvoKSGvW0bzrXXTfsM4t7gPeCk\nFKQV9DV5QTcJ3PM8lIKpqULlmgzrKWHdIJUyec97PsTo6Chr1qxl3br1XH75Vdx665tmte9Wvgv5\n/BR/9Vd/wWc+8zcMDAzwj//494yOjjJv3rxYa5+TpNvuO41LuvXTbycm4smU4q5ftXDUOlo/DsII\nNBy8OT6e71oEGuaCgygiLtme/nzao7qG7ftgB/nHB5XiknwRM1K4Cz9vCL6nnp5MU0lXiCtcjysm\nCxwTgsO6ZIXrs1wpFns+R3QNe2CAQ4bJVYdfw/N9Hlu3luFyrnWXDLxehVJo5SLdhvJTmHCcmruz\n8BWqVIRU1YdMjIxgff97CC24FI1nfoG3ZDGlrZfwf960neN33M6h4SFu/+rXeOP3v8/U4iWsf/s7\ncVcu59BknmHLICM1NE1iGTp5w2DJQG/wKP7kk7BnN8o08H0f60cP465bj1q4sOb9xyHKIvAPmRQn\nhEAKwU22zU0NCrKnW6erGnhyfPGLX2Z0dIRDh46wf/9ehodPznq/rXwXdux4ibVr1/PZz/4Pjh79\nJW9/+52xCRfOUdJth3akWN844fs+PT2Zpts32APtFAO1RSy7UpCb7fFHH/dt26moKeKlIlrbXka9\ncjsde3S64FA1VKl/avUFTKAQrkeP49Z8I5lMCssyUSqYCt3Tk67xYWhkF7lMKZZF8vfLleKD+RL/\nc+NG+vfs4/ULVvI/37uaoxs3VdQMGrDSU6zyXIalZLnnVZoZnK2XoL+yEyFk4EO7ahXMmw8R/ay2\nbw9ichL6+kEIhK6jDQ3xjKFzRNM4rGnc8fVvkh05Rdb3ufzwYazv3Y/4nY/R6/v0egpbBSkaVyn6\nSjYnPC9wZjs5jKnrFctITAPDLeH2ZmuKd3GI8jHTYEzKSpvz44bJlY5Lpu5l3SbduOmKgYH5LFiw\nlCuuuKor+23luzA2Nsrzzz/L5z//j6TTGT7+8d/m4ou3smrV6lhrn7ek24hcmnWpCSFmlAOuRzMD\ndK0sVZrN+kJQJluz5nHfsozgop4FqvaNVdldNtutOby10A4dwHj0UYTr4W69BOfq5mNyfmzqPGUa\nKAVbXJcrXZf9ukZeCszyhfjZbAYf2OS63B2p2CsVtPBOTes6q060CO0iVcSLITrVAmDPwQP0H/Jx\nXA939RqO9fVh+6pCuh6wxPd4Q4OUhr9qFfn3vg/z5Z2oVAr55ttRqvrFWj/4PsbPfsrE7kFeyl3E\nc2++g9zrx9m0bj3P6Ro/N3TSQqBPjGMLSb/vkRUCbyJo+DCAuwtFflQeG7TBc7nc9QJjdsfFX7UK\n9dMnEWHDgGFgL1qC7vk1BSuAnp5MJYJspKt2RG2Y4QlFEUGmLgV2vnSktfJd6OvrZ9OmzSxYEDwx\nXHrpFezZs/v8J93WrcC1/xYl20bOWbNtPY0zbaKz5auRdK0Wefrj/mx8HcL0SiP7xtl6OjTE1BSp\nr301qPoD8kcP4ff14uU21WwmBLwmBT83DAyCq/0VXSfrKRzghJT4AjLKZ0V5rX2axvO6xhVt8vGN\nJ1rIipTNsoyyrlTDffllss8/i9i4Ac31kC+/jHvVVdzm+ewzdKaEYJXnsa2Vqf6KFZRWrAAgpRsQ\nTn44/jrGs8/g9vay88or0U6NMP/wa3zv7e/kG4sDU/UhTdLjK4aXLeOCQ4eChg7fx1+6tEJGFyjF\nB5p0nnmr1lB8510YLzwPmk5p2zaUpmPna29ECxcOUCrZZeVLMO030HVXnwgu93xeodous8LzGWhA\nhnF1tWc7Wvku5HIXceDAPkZHR+np6eHll3fwjnfcGXvtc5Z0WyEk0fBxOYx4utkVpZRC0zRSKaMl\n2YbbdpLzDAmvfg5Z48eszn0d6h3FuuG8L8umKa3WkseOImwHyhOVha6jvXa4hnTD63hYyupARgim\n4aYMMgjWez7HpOCQrrOiHGFqQpDv0EM3RDO7yPSOnVxz+DAvrF7FmBmkKnKlAnfMX8B9vs8QsNvT\nWD6V57pvfAN5ahi/v5/j77yLHf19pJXictcL5FvFItoPv4caGsaaP5+xDRtxpUS5Do5jM9Xfx7EV\nK9i9bBnzlM9yz2epr5gCdrzr3Sz95jfRnn0a5Xp4ixfHL37lNk27qdVDCUGxaNeQZegtEhastqQs\nfk/XeF6B4bnc5AhEumooH33dmVBCdFuj28534WMf+zh/8Ae/B8Att2yfZobTCucl6YZRC4jYBtyd\nyLSC1EUwILPdaJ/o2nEhpSCTSWHbbss5ZJ2uHeohNS2OSiMemYcm6oYRzDprlTdVS5aipKymAMoE\n0ggbXY9HlY8bpk6UYoHvUygXsBb6itciWRWhFBe1nXIcD3s0jaOaYPXyC9j69DP83lNP8eS8+ei2\nQ271Wh5Jl3jFMjE0iTQMJh55CGvodQylmDj+Ojt++H2e+sAHcJVir+vxnmKJ9De/gRw6jub7DL9+\nlMc1Qd/ihXiHXmOoJyisPXPBCo4I6FeCLLDW83hVkxzIZvjGjddT6Mnyvl88TeavP4t44lFkbjMv\nv/ktWFJyoe93XMosAF9NW0wIAWmLtxWLFTvL2hlvQSSdBm4sPxVoho5eo6kNmhs0TSufB3LWQU4w\nkPLM1BSklHzyk5+q+dvq1WsqP2/ffjvbt98+o7XPK9KNRraN8nmtEGfCb7TxQCkVO3qOm74Ijz9o\nyrApFtuPYY+DqD44UFHEmWDRmsyDSNwqF/RsRkcnse2wFbSaN02lMlUP23l9uO95D+Lhh/BtB2fT\nRXiXXlq/ZyAgnXvzJZ60DHwVtPEOSclDUqILgVSKdxWL9CjFCII+FMekZL7nxSafCQEPWCaTQrLM\nDzSuzxg6PzGDQZA/u+JyRvJ5bnvqZ1z9+gnsm2/G7ell2PfwXZdSOasgjr3OqO0wTwh+qWn0jJyq\nTCU54vk4ps7AyCmElCjP56Bh0H9iiL+7517WP/IjRiyLoSVLuO6hB7n9+9/j1KaLGH/r21jiethK\nsaZkk95/gCPz5vGTTIq3nBpBDQ7ysoKDuuTl227n9u98m6uHT6GWLqV02+2xZqQ9aJkc1zR6hGBK\nCO63LD6ebx1ANHsqCKPinp5suUZgIYSc1m3XzES+EaTspFPu3OhGg3OYdKOkEB2aODlZqEiFOluv\nuTa2tssraDzo7Q3Nw2eP+jlk4Sywzo57OkLJWthsEFbyZ4tq2qOaY45eR83ypoaho2/ZgnH5ZZi6\njqFJiq5HxnGR5Ysy+lYWKcWdkRvPKt8jo2xe0yUDvuIax+WAJvl6yuKXQvCkAVe4Lutdj4OGTlaT\nXC+gr8k1/rWUxUlNQwCnNIkO/NTQGTQMFLDM83n6phvZvv1W8mVDcIB1rsfzho5e/v79efPInBjC\nFQLX9xkd6CdfJi9HStSJIfS9e9DGx9CWLEFbfgHewvmM9fYgEGQKBe75h39gKptFT2dY8MLzLEyl\n8W+4ie+mLUqaxsn58+ktlZgqf0BDpklR05j3y6Nc95m/wDt6lNLoGNmVq0AKSre/ue33OCVEzRk8\nKQU+nXWzhQjbeDOZNBMTU5WW7jA9Efo217b91uqr61E/qud8QC6X23zOki7UOotF0widqhGgMXlF\nu7xKJaeupbazRoNGaFbIMmY5caTeHyGcOhxWquOj9g3WTgRunvYYEYJvpUxOScECX/HrxRJ9vk8p\n0n11QJN8K21SkBp9QvI+XWNt2aVKqapEJ7www+LnRZ7HRZFC6DOGQUkIXjR0bCF4xjTY6LjkZDBd\n92A6xUfzRSQwBbxqaGR92OR5DEdSHRLYIzUGdQO7/MUe1CTL6iMtpdj8yCPc7Tq8uHIVCzyPq+ct\nQC1dij85ydKBAb595934gK8UFxcKzPvbv6XUP4AcPon3yi6s5Rfw9Fvfxju//GUG9u9n6aFDrH71\nVQ6tXYs9fwGZhQsxhofZ5PvcrxS/sExGt2zBn5pCP3aMX3/yZ0yuX49QYOenmPfa4SBUGBtFLxTx\nli2P9e2u9D1eUwHFhjeZ2elganO60RRFIfJwFW37tSyzUrisd6cLIt3zi3SBvzxnSTebtZBSNBwH\nPls1Qj3ZNurymlkrcHAShXPImhmst9PTNjuO4LiD/OpM/BGmrxv8HD3eODny76bMSvPASQ0eSFm8\nt67C/iPTxENi+ooiHt/2PD44PkU6bWFZJoVCqTLxtadHj5Bw1Y+h6Hrs0iVPGTquCFISthAc1TXW\nq0DOtUvX+IWhs8n1+Pt0ClsKfKXY5Xr0+4oxLXiTikATvGp4mH3KDzSzAwOsqnuv5kMPYjz/HJdL\nyVVf+AcAvIu34JsWhQ99GPr6+ACwq1iiVynWHz+OGBuDbBZ19TW4jsPE+g287isuPXgIlU6zeugk\nvmWxfGyM4fnzkSOncFetZMmieaxXih8rhdRTqJTFI299Kz8oFrj9wAF29PbzyqYcV5wcYuHwMP2F\nIsJ2UH19sb7jG20XgWBUKTzH4baYftKtMBubyHp3usBYSjB/fn9LZ7LTZXw/W+RyuX8B3A38GnAD\n8Hng8nOWdKemSk2NzGeCkOgyGaMl2Va379TfQZUfsdqrBmYi1wrNYgJ/hKmGBcFOT04pZTmN0pnK\nYaJuH+MN9mnX/SlU2CoVHGcQFdcOOwwLpKF36zd1HR1FHpgEfM9nqfIpEhiTvyKgqGk8Yho8evgg\nl+54mdHVqzhyxZW8bOj8Rr7Id1MGD1sWGnDLiV+ybPdu5psm4+k02T17uOmiiyFd1Sxrh19DaBrk\np5CnToFl4gmBdGyMJ59AFItkDh/m5oMHcFavRi1eDLIq/zvm++xZsIBlpsliTcMpy75eW7KUgqZR\nSGc4tWYNm7dexokDr+Hu3kVfbiMn+vtxe3qZymb4wgc+wDXAtYUSxkMPklmzhst270YIgbd4CcU3\nvyXW9ySAba7HAqUY6gLhht/TTKPTene6TCaFpmkRHw69JkXhOB6PPPIIY2NjrF69ljVr1mHM9jGR\n9r4Lf/7n/42XXnqRTNlG80//9M/o6elptNRngLuA3wX+BfBbg4ODk+cs6cZtBY5zAgRTY2U5Qoxn\n6tIJgYWTGlIpM5a3Q3zlQJAPDk1AuuWPoGla2e0rMP5p52XgAo+ZGqPSZIPrsdj3OVh+dPeBJQ0i\n43WuxwuGmNY62wy11XTwRkfZNXaKrG1z4+JF/GLdOhZKwTVC5zhwUgVG5Zs9n+zePRwfOYV15DAX\n73iJ0tQUL27bRp9S7DAMrHJuc2exwHUTkyzUNS4YG+OqfftZ19OHGuir3gmzWRgZqR6XXs2RG889\njzA09MFdyFOnkK8fw738CnwrhTJMFIKhizZzaNs2UApX11n35BMwMcEG1+UX73gnYmqS6x2XeT/7\nKfL469w8OspXN+UoSYnIT4Hs5YTy+bamc6/j8Marr8F87jk0y0L19SHe/S56Fi1o2/oc4mxuZgjX\nauTDEZjy6xQKeX760yf43Oc+x+uvH2P16tX8xV/8NX19/TPebyvfBYDBwV382Z99tu0E4MHBQZXL\n5T4M7AT+anBw8Ek4hwtp7RB9nG+G6uN40JteKJRij+yJQ7rROWTVxoz48rVWiPouBGOD2o9mabdu\nKI4PSTw84dvhy6bOa1KihGCnoXF7wcZUihGpsbCsCqjHbbbDPKU4IQXLPb92DlgM9HztPsyrrgQp\nWXTgINcp0C9YwTW2w9Wux2O9Pbxs6SAl2vgYA7qOqWkMpSzE3j2M3HIrX8kojkdaW5Vp4Tslfvep\nF4LfHQf/xReR3/oG2UIR56prKN50M+n7v4NwHPyly/AWLQKl8E0L1d+PNjaGmJoK0hOFApw4gT4x\nQemdd6LuvpOM7dN36CAXPvoTTvo+w9deSy5fZKMQbP7lUfK6xoBhIx/9CcJxuSid4g8ffIj/+OY3\n43kehWwPLoLHBax1XC5zPLL5IuKiixFCIJ9+GrFsGdY118ZqfY4rk4yLbq4XGu83QqBQsrnhhm3c\ncMM2pDSx7RKvv/46PR1M42iEVr4Lvu9z5Mhh/ut//c+MjAzz1re+k7e97Z2tllsNTABX5HI5Abz7\nPCbd5oWuKNkGj+OTWJbZtbxQdaBkdQ5ZT0869vqtCD3qjzAxEZjcBGPYY61Mowi61hYyKLwFRtvt\n8zclgukKBkEOVUOwV9d4V8kmyJLCMSE4qUnWuh6h1YsArmlI6MExFgmq6wOqdrw3AJ6HNnySt7z6\nKvdffDEl02Tl68f5zXkL2K1p/I9MClvCIV+xrmRjIMj98iiXDg/zvGGw0DC5QpOobAaBQgeU73Pp\ns89w6wPfQz9wAO/CtTjXvQHrxecRfb3I8TEyn/lzvHXr8C68kPyHPoxavAT9lZcR+Smci7dgPfoo\n2sgIKpViyrYZUz7PpC1evPF6svP7+bXvfhfTdtl25DDWk0/wxBvewImNGxk9eZJXPZ+dmy/C0Q0W\nTUzy4aeeIjsxAa7L7Xv24ukP8aVLLuGXF1xARinWAjsMnStGRhCFPKRSQeuzkDj7DlDKba58XNG0\nTNj6DOVWYd8vO3e1bmyJgyDImdUSDdaLr/W1rFSNlnamaOW7UCwWuPvu9/Cbv/k+fN/j93//d9i0\naTPr12+Ytk4ul+sB/hZ4O/AnBGmG3zrPSbeWYKpC/irZhidJJ8WrZtvXj7CpH4szG06P+iPUF7M6\nmgbsexhf/xry4EHIpJF33YWZ20ipZNfksOPmlXXAiHC5onZMzJOmzmOmgYbAUD7vzZdYqhQ+8LKu\nUQK2uB5Rp4fnBHw9m8YWsMBX3Fso1sq+NA2/r5/LfnmUC08Ok9d15q9ew8SmzTxkmWhCkEWwAUWP\n57Gtp58rn3uAoVIRK53mlVu3UyqWUMC1yufxlMVFP/85V77wAletXYu1ZjX+8DDmz36KOLgfsln0\nQhGhFL7rIvMFUo/8iMI978PdsrVyWKXbbqfoujxw1ZXszU9hTU1xbNEiigsWkJEa/2bVKhaOjLLE\nNDhx8WYuPHSIEU3jx9u3M97Xx/qxMTYfPcZEOsVDGzfytlIJb8UKtAMHeJNm8NTa9SxyHPqEQOo6\nmgJ/YACVSiPKUkfluvhLahtOqrnS6a3PqVQQbPT39zZQEATRcdy23iDK7a7Zzdnmu2BZKd7znveS\nKtt1XnnlVezdu7sh6QL/FXhgcHDw6Vwu93HgKeDWc5Z0O8m5RsnWtu2Guc/ZTJtoPwmis1bg6Nqd\nKgfa4uGH0QZ3oZsGeqmAe99XGP/9f4lq+N5j2FcC212XB00dR5PMcz08FJ/JpNAVvKZLFpQ/ak9I\nnrAM7i7afCllcVjX0ICnfJ8P54ukCUj7h5pEuoIUMCUFj1hmjV4XIH/nr/Pwnt08v2gBqqeXiy9c\ny/Wejy2CzimAFLDSV/SuXMF//6M/ojQxwUsL57MKSR/g+gpDCLaXHHKvH6dPQeG555DDw8hjR/G3\nXoKu6Ujbxjw5BEuWIJctwzcNXM/lxymLHUKgAb9m26xF50vveTevGDovGQbakSNY4+OsPDnEcc+j\n5HlYp4bR81Ps33IxGdtGKcVEby9jCxcx0tPLq0qx9fARCvMGuP+a6ziUyZC58UZuK9q8SSl+6IOn\nCTQUN9o2pFIU7/p1zB//COE4uBtzODGctsImByEEUkpGRycAanS1QbdZdbZZ1AzIdd1p1+DpyA+f\niTbgVr4Lhw+/xp/8yaf43Oe+iFKKl156kTvueFvDdQYHB/955OdDwFI4r3O6qqJXDbumWhWaOlcj\nBObk2Wyq5bywmawfbjsT5UDrdRVieJhUJoXnBZIdVZpE5fNBgah261hrCiG4yTS43jQYc112WSY/\nIsvxrQEAACAASURBVPCOLfk+uxFc5zqI8sXjIzgoJa9pshIR56XkaVNnm+3iqqqSIUSpAfnvWrGC\nZ9avRS8XwXYoxZqizWJfMS4DnbarYIPr8bBlcVyX7MlmcQTs9RUfLRRQwHNmUAgbX7WagS98gfzJ\nIbKUH5OHhrC3bsU8fhy3VMJdvxFZLKLt2cOpzRfxUimPt3gxtq94wLP4/bEJhsfH6U9ZmP39FJYu\npYgit3MHEz09FCyLBceO0Ts5STqfx8lksFNpvMVLWIxCpdNMrdtAceVqJnyfVzUNTQhGga+lLT6W\nL7LGK3DK1LlI1yiVP1Nv3ToK69bF+r6mf3+1AUwYFRcjwp3AVyOQctWP06kfp3S2FuU6QTvfhdtu\nu4OPfexD6LrOHXe8hbVrO/vsz0vSFUJUKvClUrypB51EulJKLMuojDOPo4eNu35YfJNSMjVVmDaf\nbaYI0xOsXEnphZdQ4cDD+fMhMz0n3Ekxz7ZdnPEptFKJ/aaBbRpIGURQ86TAtyz6pMDzfbbZDkqT\ngewq8tgafjs6sFYpdhE0LLgoNjXI/Y5JphniTEp4X77Ijy0DpGCrEKz2PB4WBq/qOr4QYNuI4WH0\n519g6bIL2N2T4fIvfoF1P/kx5tgY2YlJSKVwV6xEDJ/ktalJTm3ezOvXfIhrT40w8K1v4Pb0MIzg\nqr/8K5745x/H7evFGB1F/e3fsujyyxjJZHjDmgt5dc1qfMdhqq+PoQULEL7Py5s3c88Xv8hFu3ZB\nTy8/eN+9XOArtrguR6Vkvu9xV8nhRUOveX8jQlICBpRisYKMUrQvnbZHPF1tnPl2qcr49VBXG210\nmAl5xk8vdFej28534d57P8i9935wxuufV6QbNfj2PK8j/4I4pBgtONm2ixDEVjvEMT6PpijSaTM2\n4YYE2ej8DB3FfF8xOVmgb9s2nJOnkPv3QyqFc8dbOk421/rv1namLfc8dvoauhJ4ns9WX3GTbTOp\nCTYpwWpNQzM0Nho6R3UNoRSm53GzUlgi8B2+1/f5rm0zKYLi2+YGc9A2uT5PmgpfCDxgr5SkdIPD\nmsZbizYLNA1N05gAVngeJcDwfThxgoUjI4zlp7jjS/9Ij2uTP/QamYlJeotFevNT+D09aGOjHFq0\nEHtyEj8/xZO33or32GPccNFmjugaowhsx2bxq69y5Oqr2fjww6QmJnnbcy/wtcsuw9mzl1tKJd71\n9a/zlxeuYd2+fUwJwWhvL14qxbseeQRNCLZt2MA3L7qYMSnZ5Lq8rWiTAl7TJAeURPo+aBo9ShHO\ncu6mQmA20WT9fDvTDGwxJyfzlfFU4Wwz36+d+tzIs7fRsZ1vbcBwjpNuSDb10xTGx6cwTb3Dwlhz\n7ok6aYVNE4FOML7Rd7P1qyN9qsMqhaDDcekhoVdP0KhcLaoNVoB7y3a4Je6aVcTJL1/uekxKh92a\njolie9FmuVKBmBco4EAB7gRe0DU8TeMqAT26jhHpQrpLCNzXjyO+eh/+qVN4CxZS+PV3QTqNtutV\nljz3HB/uzfLoLdt5Zskilvs+JU2yH8mf9mhcIyWrhGAL8PaSw08Ng1OFPP0njrNsYpILRscCZ7KX\nX4FTw2ijI0ghUOkMuA6nli7jpzfeiKdr9Hoei/bs5vBAPy9LgV8+r1zXJd/fT7/nc02+iAEsPTXM\nv/zsZ1ATE3hbtjLS14u7ZQv+yZNkbZvsiRMscF3MRYsQlsXKYoHf781Wo8IUOI7H9h07yTz1U46b\nJhO5TbxxyyWIivC/sUfIzNC9tcLItJWutkrE2YZdhtGo+Ey6jJ1OnNOkG5JhlGyjfd+zGcMerl87\nCbfa6TWT9aM3gWb+CMG2sZetbB9GP9GIuVBo39jQbk2oJ/DW+WUBbLNdttF6v5JgNhnltSbL0ZJl\nmaTTKfL5AumvfRV9ZASpacixEbKPPYJz7XWI7z/AJIKeYz6/sXsvQ5/81wxlMuzRJIelRAHzgd1C\ncNLUeaPt8odTBR5yHbzDR7hwdJQb9+9HCYG3YCHma4cQxSIo8BctYmTLVn62ZjVoEoUgrxSvGyZO\nbhML9+1j+c6dAExcfRW51Wu4oVBEu+wy1O5BjN27kRMTeAvmQ38/81/eyYVLl3Cspwep6/iex6Un\nTuBYadz16/HQsE+NVQgplbLoyUjkn3+aO4dOoBT4qRSF37yHwjveWTnvhpTi2+WJEZtdl8tmmPPv\ndtTcLDINdbWNugwbGeI4TmB+FPpJt5r6fDa2ALfCOU26vb3ppp1YsyHdRpHz9PU7L7yFUXk0ap6N\nP0Jk9XJjQ5hnbjXePX6nHkDP/8/ee4fJUV3p/59boeNE5SyUkIQQOUeTbDDBYDBgLyzJNhhjf73L\neoN3fz9/dx97vQ6wNrbX2BgkvNhrWFjnJZpgTM4gCWWEJJQ1M5rQqcL9/nG7uqt7qrure3oURnqf\nhwdpplV9q7vq1LnnvO97WuJ1BPDGsqYc8FREGc0cJuBwIJezMLfvwLF977l5GyxfzgbD4H1dIysE\nrY7DqN4enu7sIIWaVhvr76f7vfcYY1msGzMW4i2MlpIr0eh+/Q161qzmLcOg88gjmeq6ODu2o0W2\nIqXkzWuuYdH1N3Dwz+6lrasLE4feceOYsWwJJ7/1Nvef82He/ej5SCFIx+NcmC9fOQfNIPUXV5P8\n3u1onZ24kyYrgURLKx9ZuZqn5s/DHDeWk95awvgFC7EzGZzOTjLnX4AsC0jakiV0vvUWwrYRho42\najTxlctpGXudYh1Il58JjV7UlIb1ukZU5kqMgMJiOBRkYVHJEMdTh3qGUC0tpaPXvYy4HpvIelBL\nBuy95stf/hKnnnoaF198WV3H36eDbm9vqmLgqzcoelDNoUjNseP1m2yoSRNtbcmq/gj1QjmqCZLJ\neChD9bDHjEYjhUZh1bp1Xx/mH36PSKVg0mSyH/pQXR+8BO6LR9mZt1h8TRMcognGRgzOHj+e+MaN\n6niuizV6NP2tbayybXYIE1dIdjoOa/JS3Kim0ZbN0NnVxU5dZ1xXN53vr8c88misZAu7/vQUG1wX\n8p3+vq6ddGoabccU57T94YwziSeT/Obmm5m2bBmjUgOc8sgjLG1r48H2duRbb9B7/Ano0RhH2DZT\nXIeXTJ02F+ZNnox1+ocwly4tpJAbx45mbecoDurqwujvI2vnyFx3PXL06MDPSfT00HLHd9F2bFdB\nLB7HzVmkkm2kt+1E13X6k3F6omr6r6YJEkKwIxahzSpVnYW5vuoaryMl5ssvoa9fj2xtJXvW2SWW\neM0K4I7jIqUKqB6VTQk4/KPXozzxxON8/etfZ9as2cycOYdZs2ZzyimnV/JBCI1aMmCAu+76Eb29\nuxo6/j4ddKsFVo8yFhbetF5NE03zMADyW6RIYUZb2GPXykj92TjIfI21dqZTrekmRNGY3LIsHEfU\nbBR+8L+/Y52uM06DQ155CakLcqd9aPALMxli//sHRNdO3NFjyJ5/AUQi9AvBJl1XnFxgiWGwTdeY\nEYmw6i//ks/ffz9GTw/bJkxg9UfPZ5TQeLVrJ9PefhtH03jynDN5e9IEZtk2sx2Xvk0fsFwohVki\nl+PC5ctpmzwZ44Tj2Wxb6BGzQG2KpFO8N2kih2/brj4bx8FpSaID8yWsW7iQo+65m1WTJim1XU8P\nmmUzYfMWLh87np5clntaEtiRKI6UrLZtTjjvfHojETq2bmViazu/O+tM5t33M7RsFt2yeHfhQsYF\nBVzbxli6lNgD/4X57jIEQs1T0w3kmLFkLlZSU8dxiNs2mq6R8XwogKjrYqPq7olELJDS5SnQSr/z\n8IHSfOF5In96BmEYICVa107Sn7qqoWPVQvmoHikHj14/8shjufPOn7JmzRrWrl3LCy88x4QJEzni\niKOG9N7VZMAATz31BEIITjjhpIaOv08H3Wpw3XCZqH8OmfIwyDXtwvGbfQ8MZIhGzdDHrhYc/VSt\n3t4BkslYHcnl4KYbFL2JvWOqkUHV/XffRvLIzJk4us76jg7mb9nMZ9euC+RoxH77G4z314EQ6N3d\niN/9hsylnyAiJUb+ZLdqGo4QZFF9tx3RKGsuu5z1hsaf86o2ISUrP3o+j190EduEIKtpjHUcDFey\nRhNMi0T52Csv8xfLltGRy2EPpOiKJZFbd+KOnYBcuhRhKolzZuJE5l1yCdHf/BZ3YADroBkcNnkq\nL0hJv6ZhSskhW7bwxvjxQL52mE4zkEySfPxxnrIy6BMnwpgxiHnz+XPEZKlhYFxyCY6UHGLbShDy\nuZuZtOQdtDGj0fr6ifzpGeyZs3Cn5restk1i8T1oO3cSfepJRDqD29qCyFm40QiZ8z6KHFtUmSWF\n4ELH4fdSYgk42HI4JpsjVfaZl1slBgkdVPMr3JWjv/eeCrjqw0D/YGNJ5tPMoZRhArgQgrFjxzJu\n3AROPvn0prwvVJcBr127mscff5Svfe2bLFp0V0PHH7FBt9b2P8iQu60tUdfTulI2GnRsXdfrLkeU\nB8dy3wUvE2hEeOGhEv1LytpG8K9FTNxolNcmTCBrGGxqa4OxY7kGpQYzX3wB45WXcIXAWL8Rxo1V\n/1AItO071DkBZ2Ut/hg16Qe2agIpBDtNg+m2Q0xKXjBNDARTX3mZWX9+lqPa2nj0nI/QM2cW7Y7D\nJNdlhpR02i5XxJN0WjZJK4dmGGTPOAs5cSIAkw8/gq5chl3vvYcTi9F+5jmYbe30X//pgj/BpYZB\nv6bxmOsyVbo8fd55JJYuxZESTUrs0aM4yLZZtnkjLx93HNtbWjhoxw60LZvZMnGimpArlHvaEkPZ\nR/42kWD58Sdw4pNPcOpTzxDRdcyXXyRzwcdw5s/HfON1ZROpachoFJHNIiNRME3cseNIX3X1oPE7\nR7iSWQNK4FGJo1NulQh+oYNBJGISiZhEoxFaWuKF0oSXGQ8KoIl4yQXkxhMlF1OzM916doTNRDUZ\n8COP/IHt27fxxS/exJYtmzEMkwkTJtWV9Y7YoFsJpQGx1AC9/uZYadAtH7tTSqmq72L0r6XaqPTi\nseu78Mr5u40cUwM+OPRQsv19aI6LHo8xMOlQlmQtjlu5ktfWvcfTp52GrWkc+vJLfPy996GjQ7ly\ntbcVjMNHS5eohKwGEVdCfmyMI2BM/rNt2bqVQx5+GGkYzBxIcfOvf8X2T99AJNnKLCmRQJt0aZES\n68yzyV1wAV26zqaBNNO2b6f1t79C6+3luLHjSX/8Ushr513/RAspMV97lY5dPZw4fTpbjz0GY948\nZCbDMWvWsG3cOEYfezyjtm7hd0cdhQ5sam9nwNA5ZOlSZm3YQMJxsOfOU6ITYKqU3DyQplcIDn79\ndXL54CmEhvn6azjz54PrQDqNSKWQLa242RzuhPG4o8eSvuZa5PgJJZ+7d82Jur/1wUKHzs42BgbU\nfeAxKJLJUlOcQmZ83kfR7vtPxPZtEE+QPe/80uuhiV4JQmh7jKNbTQZ8883/p/Dnu+/+MaNHj667\nzLBPB91a369/i149IHqvb2QaRDj+aiNsCsMwSCbV+JrmmZ5LEgkVcMJ5+1bGqZbDGy0tyM4OEILp\ntoMuBGNiUTQ7y1OHH4bhOmhSsuyYY5hkRji+pwd31GjWX3wJDyVi9AjBO4bBwY5DBMEooB3JDMsm\nKdX4mMMtm+0bNiB1RSfKtXfwyFFHMrW7h2Vt7URclyMtm7OzOdZoGu1SskLXeME0sBIxxmzZyGf6\n+mmxbPQPNhL73z+Q+filgz7ExO3fwXzzDSZPmUzbmLHEurtZd87ZxE86mZOnzUBvbcWIRPivWbOI\n7NpFTLqctGUzmzMZLn/3XcbYNouOPQa5ZjXpzmM51rILUudxSAxNo0Sqkw/A2qZNGC+9hL51M8I0\ncZMtWIcfTvaCi7CPPpZyNFM04AXwovx3sCmOaebH6kyeiPGVv8dOpbE1jajt4reKbP669sxQyloy\n4KFinw66tSClLGyfwhjGNLJVSSbjSClr8lfrCYyGodRUiqqVCaFMC5GV5odrKif+2kq9kvVaFtra\nNciWFuTkKYD63YJYhNtMk285Nrscl7jj0mHbTE1nWT12HPbGDegSuuMJsqZBzw3XE2trU47/AtIS\nDNclpQvWCJ0pPbv4IJcl2tnJRl3HROfORIwzszmmTZ7KWNdhdH+KhxYsAClpSyY53nYwpOTydJbF\niRi9mkYWyVbTYH5++QOu5Ok5s7hg6buKxrVrcNc58uQfibz4PJrjMvu9dbwjNEYvX8a6c87mI66L\nTLZguxI7k0XGImQnT0ZfuRLNMDhICA7t7UXXNP761VdZPn48HaeczFRdxzb0fANLIk87DX79W1VG\n0HW2nnwKK7ZtYd6K5UwZMxo9m1HilfmHIOJJ7COPrvGdDx3VSgLVJv8WJzkUpz0LQYEjHsZAvRrK\nG2nV1t/s8kItGbCHG264saHjj9ig6+nAIxEztGFMI/4I2WxYqXHtY/uFDa7rkMlYoaTA1QK6nxec\nyeQQQoS/GdauJfqz+zCe+zNEIjhz52EffSz6pZfka8s2Ru8AfyclqzSBZdvMsmw0YGL7KEzT5N1M\nhk2tLciWVsyIycK+FBN0nXQ8QjT/YBklJcaWLfzFD3/Ie2PGsGruXNYfdjiTOzrp1zR+F4vy+ZYW\nOs0o0SUvI6ZPQ44fD0JgvP4aRs5izfZtpC64EBOwEWzUNGZ7N20igSPylU/XHWR9CKBv3ACGCU6W\ntlyOE1aspGvefE7LWrSaOr35120Wgvj76+nt6SIWjxPP5Tj39Tew0hlsw0BPZ5g7ajRO7wCWj/Rv\nmgacfjrG9IOw129g84wZ3D1qFGOWLydumhAxmd7erkoGUgKy4lbOC5T6229hrliBjETInXUWsgHz\n7kbEEZWsIkeNasd1JbFYBMNIFLi1fneysNzaPWV2szsw4oKuV6uUUvH90unwW+ha2Wi52isSMUJ3\na6tdP+XqtGzWIpkMLzFWKFfTkaeURUp4wYYRsqEnXfjl/ejLlqoJCOk0xqYPiEZM7A+fRZ+VLJy7\nBsx1JZbj4n0aUeDSZBv/MGkSHcA4xyUpJc8IwUXpDGNdh6WmiQ7M1gTjX32NdiE4q6uL0bt2EV//\nPs6ECWp4p+uSWrWC0QMD2Mcey9FCY71tE3n6aZxcjuPfeotxO3Yws3MU751yCjGgXUpslPWkPe8Q\nDl+5CqezE3f8+MDx5LKlBeeggxArViBsG1paMD90JjHfR7VeF9wfjWJm0rTmckzr7uYvXnsdM5sh\nd/oZaJs3Izs6yJ3+ISgj/eu6TmdnG5nOURhjx7Fu1UqOe+qPqsSQTLBl+nSm7NqFIcEZM5rcUceq\nqRcrliNsB3vuXMg3c4QA8c47xP/3D+pnUqJv3kTqszdR7+BAdS0MPbh510Iq5Z/KPZhb61ecBU17\n9q+rWUyIvQ37dND1BzIvo4BirTKZDD+tQR0vOBsN8kfw3nMo9aQi13awOq2eUkf5lIwiy8FumHMs\n0xnEQD84LkLT0HUNmVOqtHR3L3J8vOYxOqVknu0Q8f3MW8lHsxYJKdmu6YxzHc59ewlmJoemaUzt\n7ubFiZMQlqI0deoaM3CJtSZxpeTI7i5GPfUka7duZZxls2DdOnoiEVpXLodTTkECF9o2B6OxM2ex\nwHYYc975pAPW6GHNR8/nxWnT0Lu6OHrDBqadeTZy2jS1ZgkMDJD69f/w4Z3byaUzLDn2WNaNG6ec\ny3QT6/gTqgY8lVFKMpkc+trljP+fB5EREwE4psm7Z53NgqOPoa2tjeT8eURnz0Hecw/u2rUqSL3w\nPKlrrgXTRAiBtnJVIQgrNsh2RF8fsr3e2WDDp0gL4tZCqQ9DpWnPhqGFlrAfkAHvZnhbfUWhzJV8\nUdVG9gShHn8E9frGpMCgeLFF5VtqyDJjKLIcHGcwM6Pu48ZiMGYMxvQMomsnjm3hxOLY06Yhx44N\n/CdCCAaA100DHTjWsplv2aw0lC+skJKj8w8sDTgzZ+M54ThHHoH5xBOgaRy5cSObFixkac7CkJJj\ncxb/fdBMFjiS6bZFq6ZxUE8Ps9asRega0jAYbVl8KGsRdV2itsPphkFEh74Kcmg/+gXcP2Y07hln\nIHb1sLq7hyu6u5jq+05ijzxMy7at5HSdqGFw6J+f5dkLP4aWzZI98+y6Mkxj1UqmAjulJCcEWl8f\n7bNmY42fyM78a6KvvEp8zRq0SEQ99LMpkmtWYJ1wEoahK/aHlEXz+WgUGat3dzQcMuDar6vmw+DV\nik3TJBKJ0NKSqNudbCioJQF+6KEHePjh3yMEXHvtZzj55FPrfo99Ouh6QTGTyQU+FRtlI4T1R2hE\nCqyCrRkiCw1PAxNC5EsdMj/8slo5pfZxhRDEE1HEdddh//dD2B2jwLFxjj0e56STKgaYFHBPIk4m\nrwRcahpcm8qwxNEZ0ARzLYex/vNNpYj8+VmEZZE7/AjSl11OZPMHGLNnceqq1Zzxve+SNUwWn3su\nWw+ew6obb2TmC89zVtYitmABiZ/8GGP1ajTpIMeNZfR553FJfgsLih6lLAXL1FiZDNHHHkX09eFO\nnsz7Z52FJQTGjh0YK5YjhGDj6jXMXvMefPzj6jPp72Oa49KjadimidbRydEzZ2LdfAtua2vNb8q/\njXdb24g6DkcDXUIQdV30eLJkk+9kstiOC95DQ0qsrl2QztDamsQ471z0ndsR69bhGia5D3+YeEdb\nYdseFo3UdKsfq7GDlbuTGUY7/f0pHMfxuZPFME1VHuvu7uFHP/oREyZMYtasucyaNZt4vPbuqxaq\nSYB7enr41a8eZPHiX5DLZbnqqss56aRT6s609+mg67qyhv9C/UHRMML7I9QzV02NNFdP80pZaOmx\na2ekXo1Z1zUcx6G/P4yZevXjFr0ncsjOTlKXX1nzmB5eM3QymigEoC5NY4WhB0/6tW1i9y5ibTpF\nStOJrVzOxCv/AvGhM0msXYn53HMIw6BHEyx86L/Z+aW/Ij1qFEvPv4DWbI5TLJuBz9xI9LlnwXaw\njjoaZ8w46FLMhJaWRF6BJUjEoxi4iFgcS9ORd90PGzbgSomzcQMzpUReeAH65s2q0ahpjM1kMNas\ngY9fAkicSZNJbNnC0UC3AG3iJAY6RvGTWJRuXTDKkXw8k2VUlQvG+5V1wgnoH2xAX72GMYZO7oyz\nsdraSj+eefNxX3gBrUeNe3djcbJHHAnZHMlknL50FuuijyNsGzMewzANIqbhm+rglHJsfROAhwPN\nDN7qeKqmWykrBsmECRN5992l/OY3v+b999/j4osv4wtf+KshvW81CXBHRweLF/8CwzDYvHkTLS0t\nDZU29umgWwthg6Io8UeQdfgj1A6Mfg6v19gL0yCQkoreEf6yhzd63VPMNAq/2s07/2hUVWNzwDu6\nhoFkoSNLFFCrhGCXJpjnuGqqLsU8WkqJWeFz1D7YyJreXnbEYwhgAJ3Nq1Zw4tQpsPGDgtw0KkFL\np2nduoXug2bgSEkyf0w5ZQqZKz4ZeHzXlWpk+TPPIn75c5xsDnfyJNxzziG66QM0wyCia4h4jFjX\nDi4wdH7ZkmTANGhPDfDW5Elsbm/nHEBIyJ11NggNbfMHdLa1k/3Iufx3LMIuXUMDenTB/8YiXJUO\nnucghKAP+J9YhBSCmZ/6C05MpdUEjaBr1DBIXXsd5quvgKMeKoETPgyDnGWTK9vpFS0Ti2IHKfEp\nzhqf6FDp/HbXqB7v5xdccBEXXPAxdD2SLzsMfcpKNQkwqPvsoYfu5+67f8Jll13R0HuM8KBbOyj6\n/RH6+zN55kPYi6dyJh3kQVvPGPagMkAp/atY9lDG3yGPWpb9VxN2SAlZAXdFTHqFmjf7pu5ydU7R\nwn5v6LyZHy75jC65IpXmbV1jh6aBlEy3XQ6uUH+TySQpUTxD4bps97aHkyYhbRthGHRKyWjTZMe4\n8VjAXMcN7R2rPflHEj+9G3Obsm0Ujo189HEyySR6Nls4STnJYIvtMNaxcbZvY1N7O/qUyWycOBE7\nHuVi20EzdHJnn11y/P6yD7387yXnCywWsMkwEMBGXcOg0hj6PEwT68TBaqcwAa6S2EHVTIs0NiGC\nxuuEcyird031oB6eLngsiaGHs2oSYA+XXnoFF130cf7mb77I66+/ylEhBoH6McKDbuWgGOSPoGla\n3Y2x8sBYpJWJQY29+tZe2pUdbDnZ0GFL1llUplXiMUte1nX6hChkt+s1jZVIprqS142IGr+Omtf1\nasTk0zmL5ZrAkJI5jovQRH4UmufpkJdOjxnL9hNPov3FFxBSsnP6dDaddBIP6wb6MUczZ8NG5i5d\nitR1pn3oTG6WAjmQpjUvfw0DbelSRX3LE+i1HTsQEyeRPeMMYs/+Ca2/D2fcePrP/ghvrlpJZOtW\nXN2go7uHbEcHctJkNgqBaZqMGdNZQnWyLJvJsjjLzQUmVsm0cgK2imLpxRCC9zWN40Keix+NbuVL\nJM+oa6Czs52+voHCeJ1EQo3XcRzXlxHXHsW+OzPd4UQ1CfD69eu4884f8vWvf6vQ7NsvywvVstmg\noFvbH6Feipn6s6f4qmYi3ggNrNTkZiDw6V9f7VoQiehEoybpdJZcrvpDofzd9FWriDz6KMlt25h1\nxod4//QzEEKtVQp1QR3qrTG/bVaJr8wHiqJJz6Gnnc7vTjyRHtti5dixbNF0MobGQUJj4rnncuaZ\nZxUywdb8Dbha13gh7+F6jGVXNO4WAohEcMeOQ9u2DaFpSE3DHTced8GhpBYepgZjahoC0N9/T/Fi\nNYEVi9LS1YVtO8SAjO3Q358aNHLmGtPgD0KwxXEZZTuc4zhIQw98gEUQJKSk3/e5tjXMj20Ot9YL\nbEHjdUodyoqj2L1A7B866T/Wvo5aEuDZs+dw443X4Vk7HllVNRiMfT7oVoM/GA2XP4IQgkRCdVVr\nmYjXKwVWpiMiVOOtFjxOcDRqYueDSC1ICce7Lm9IjZQQiK1bmbJyBQfv2IkmBCc++SRdM2fRxH9J\nLwAAIABJREFUP20qmpRVt8pKrgn+h1qnlFwdifF6PEG/hPWawEDwgYAWIVip6yXH3CEEv4pFC9/R\n73SNtlSGyRVuduecc3A3bcGeNRvRt4vciaeQufKTxRqq91AATt60iWcnjKdDSnoch7lbt7DDcbmI\nYg1xmyt5TUr0XI4T+20SwMlCFGlOERMj38jyTzmw8iq9Sx2X+11JWsBkx+HM0ENNB3+WzYhv1QJl\nsENZqRdDS0scXdcLjmSapj6LodaKw5YW8mfR8PsEv3d1CfD113+W66//7JDeY78Iuq2tqgHRTH8E\nb7qCrisS965dzRnD7ucdO47DwEA1Sn+448ZiEV6LmrxrO8RyFh+Vle0Ay5HYtp2bunby+uxZmOvW\nccIrr6LnjUjmAfYHH7B5wgQOcRxGNVAHFAJSuk5E14gZBq4msB2HrK6RcJySG3CtrpV8QZoQrDN0\nJlcI9u6MmQzc8gW0HTtwR4+GKpSi4+fOZ/YTj7NTwMxcDu1jFyPSGVpaEkigWwjuTURxhZrBtsIw\n+HQqQ0QGjyf35n55AgDTNGiX8E9AzrJxpMTStIYepkOhZpUep77sNMiLwVOdxWJRdF1XdDbf9F+P\nQVEPv3akZM2VMGKDbtEfQTAw0PiAxiB49VXLsgoqo/AIDo7lEmPXlSQSkcDXhkUkorL752yH3+Qs\ndAmarrNdk1xbcSU+PPUkkYcfxZBwejJB5uxz0FwbPB8Dw2TWzJnMGoKxiRBwdMTg7WiE2Y7DMkfi\nAtMdl3NsG03TCuWJSUhcJEY+07OlZLzrVn/oxGK4U6bUXIecOpVR11zL6HRKTQQuYxQsMXXc/HkL\noE/TWGXoLKhw7l4t1GOXxGJRYrEImUwWwzCIlm3Z/fSuWl34Zkl3m0Hz8lRnnry8t1cVULw5Z4ZR\nyq/1U9i8cx68Li2Uw9hweOnuDuzzQbf8oikPXslkrK6AW21MTnl91XMxq+/YpT8rpX8Va8G6rhF2\n61SeoXsPHCmVV+6yvIwXQCDZIjSyKKPxirBtePIp9FgUaTuQzWCuXEH2sssxX3kFKTSsU0+B1rZq\nR6mKaDRCIhEnaVlctquPZ3UdaeiMdV3mOC5tvq9ACMFBwJm2wwumAQJOsBwOlhLy5+a6kEbyv1GT\niY89yrQ1q5klBblzPoKcNKniOkR/P2TSyFGj0Vetwnh3GZgRsmeehWhN4rqSqFQPAy8Uu1KSqIP3\nKoSisakHdPEhrRgFnjeBUmAVJbF2SePOj2aVF4bLrczj15aea6mBeiKgFGPbDs20iNwbsc8HXQ9h\nGllh4LEG/BdQUV7rDqm+6ucNV/NdKK4j9JEBUZE5kczTvbzDxZFUy6FdV4JtY2VzGPEo0ajq0jpR\nE/vww7AXLMCxHXDshu5Zjzsqly4jvXQpdnsHE447nqxh0Ak4msaSfIPr/LJgc6LtcKI/OyqRbcNd\n0Qi9q1aibd1CS28vuu0w68EHSH3+C0hNG9xYffopIs8/B65bkNSKqKL6af/1c/ibvwEhONpyWG44\nbNA0XAGH2zYH1XUdBAc4xShwS2bR+SWxpTPPnMJ3qubYDXUa7u6dBFxuoO6h1CoyWjBQ7+hoK+EV\nD6f8d3dinw+6apZXtGIjq96R4/5s1D9doba8NhyEKJ9xNth3Ib8SwjcJBJomaGmJBz5wzrEdtmuC\nDzSNqIRL3Mo1XdeVamtnGuTmzMFZtRKRNw+35i9Az28lvWnBnsy2aFZSuYmiaRrJpMpu0n/6M+J3\nv0MzdEzHQWzZwtYrriicsQZs0TU1WiIkVkVMnk/GGWPodM2fz+b2dj68dClGfx96Jo1sbUW8/z7m\n668jhcA64kjM556FqMr5jbxNojtjhvpUu7uhayeMHoMOXJXOslUTmLI40SIs6tnKV2MUFE1iPB/b\nUhrbnqqdDuVY5VaR8XiUaDRCOp0tNMBNM1lSnnj11VfRNI3p0+c0Rf4LtX0X7r//5zzxxGMAnHji\nyQ031EZE0HVdt2Ijq5Gg6w3yg9rTFeo5vq5rRCIq2PrnkQUft3amqwJ4tFDi2LVrIPB1EeDanI0D\nRAydeCxSoC55UGtxS84jd+ll6K+8jNbXp0bQTJmC7eN5eudUpBaZ6LqBlG7hRrJtZdvn1TTT6Sx9\nfQNE33wTLe+RIHQdY8UK2qWkKx92JdAacovpBfNlhk7EccnEE8SdbaydMAFz6TJkaxuipQVt2zZi\nD9xffKgueRtsG+HVWeIxRCZTrBVGzJLyiQZMbHjbO/Tao/osXVpbJV15uXMpja3e2mlzWBDesZo5\nlNJxPE5xqfzXE3e8/vprPP30U6xd+x4TJ07ksMOO5G//9itDqvFW81344IONPPbYI/zkJ4sRQvD5\nz3+a0047g9mz59T9Pvt80LUsFykrN7Lq2abrupb/L0IqFa755h2/2sXrPa3VWBSbVGroTIdy+8b2\n9mTNYwYZUapgK/PjVspOQgic446nWn5f1MYXf+ZRi9S4oXihnmxZNkLkfSjMslq4YfCxnMWvoxF2\nAWOl5PwQJaJEIkYsFiWdzpLJWswxdFZMm0Z/NkPHzp3Mbmsn85FzQdfRl79bci1ohgFeEBUCd+o0\n3M4OleEaJvY555Fsa8VOq+9rKI2b4WIcVPIm8LbrkYiZ/w70QYG4WWsKWtdwHEv6mCKf/ORVfPKT\nV+E4gvXr32fnzh1DbqpV810YP34Ct932ffT8iCXbtolEGmt07/NBtxbC3Cj+ZpbjSHK58Eqy4vEH\nXyTlUmBQpYWhwAvgjdaXvfWWB9tmNoFd10VKldW7rptvOrqFjDgajWBc/DHEonuQfX04QsM671wm\naILPZIK9C8rhNeEsy6KnpxfXlZwuBBt0wWGORM6cxdlTpiEXHFY895ZWpOMovwNAupLMNddirFkF\nWQt74ULloeu6xBMx2hNxMhlVrlG1+KKwwwsKu7uDHqZM4Q9OfhRtE4syYG9n52dQNEZja+4kYMcJ\nd6xIJMLs2XMayjjLUc13wTAMOjo6kFLywx9+jzlz5jJt2vSG3me/DrpCCBLP/BHjrbewJfSfeDKR\n005t4CaqJAVWDIqiXZ3ecHAL8nJoBEruLPKqPO8ma16nWNc1kkk1qmVgIF1y45cEglgCccNnMXdu\nRx83nq6Odh4ydLqFxhjX5XLLIuErT3gwDJ1kUvGu+/r6Sz6HCVJyczrLek1jrJSMLgsCztFH46x7\nD2P5u0hNwzrxROSMGVj5Gi54Tb5EvmTVh+O4gcKOQQo7V8KOHWAYuO3tg66h5gWlxhkHXmD1plm0\ntibzpSAX09QrGuMETXYoR32ChupQlLHGGuFDQS3fhWw2yze+8S8kEgluvfXvG36f/TLoes2syLJl\nOC+8QA5V2zIffRQ592DEuMEztKofX/1Z00Q+gyiO3Sl/bX0y4+LUCl0vDeBBr62VBakmmaK7GUZ+\nwmtSRwgNx7F9ddj6O8WeMi8ajZBKZUqMViqeXyRCbuJkAH6Rs9npOIBgoyb4FYJr83VKz7rSaxim\n01nS6eASTQKYVylTE4LcZZ8gl06rMTm+7aG/yVf+sKh0voVA7LpEf/lfaO+tQUiJdfgRZC+4ENlE\ndoDvFJpah7Vtl0wmS8b3cZbS2MonO3gqu1Lf3j3TlGvuDqOa74KUkn/4h1s56qhjuOqqa4f0PiMi\n6Far23oUMA9+V7HUuvXo0vcPBbBpM2L8+DreWwX1eFw1tLLZXJWmHqGzaO+mbmmJB06tCDg6lWlJ\npU2y8s64R1EyDD3Pn4zlb7JSVkKlbCcWi5JIxMhmc3R39zZ08/UWPhaJdCVdrkt/XnQSj0eJx2P5\ndbhEo2qNjuOWrS+kO1ZZtzsejxGPRwtNvnqhv/Yq+ob3IU81M5a8g7NwIe7MWUCx7rxrV18+I1Tn\nCfWXJ5ob3IIDeC0aWxDHVjX09KbYRTYza64H1XwXHMflzTdfJ5fL8eKLzwNw0023cOihh9U46mCM\niKBbDV4mWjS6KbqKiYNmoD3/XKHGh2HgHnQQRh0PUJUhxchmrZo+vGHHB3mKNympyXIoHnvwTVS1\nSVa2rvJZVp68U9f1Qmfcm+7q3Wjew8ZxilvxRjHBdVmv6Qg8xy5ZaALZtkNPT9+gWqOu64WHRSMU\nttLj9zZ8o4tUPnP2/q7riP6B/PETWJZVeBj5FXb+nU/YQNzM+nG9rJ5qNDZVY4/lSxZykIF6PdfG\nnpIB1/JdePLJ55vyPiM+6CoTDjM/WaHML3bGDKwLL0J/4zWEpmOdejpmW2uoC9sL4p4MOOwY9mpb\nIu+YnuKt6L8b5gIsZrrNaJJ58s6gmywSUU0sz2RdSpnPRIuBrl5cmrN4WEK3BhMRfDwexdQ0+vtT\nFUsqjqOy73opbFK6+fVXP35YOIcdhvvqS2iOqz64ZAvJY45CS8Tp6xsIHJ+jdjI+H4kKTmxBDbu9\niXHgfaYtLUm6u9WDsRKNrTwQV7pOwq5rX5QAwwgOukXjGMVZrGQc4x52OO5hhxf+Xqvu6hdM9Pen\nC+qZMKhUBik/pvdgqOd+8G5Q13WHhZEAnopOlVH8dduiDWDR+MRxnJKsuFYgjgAX23ZJXXggJJPB\nj2oUNtM0aGlRwdZrFnlG3o127QFkZyfZq6/FeO01ovEokXPOJq3rpHt66zpOmIZdLBYJDMSNoPml\nCnWsIBqbJwEe7FBWKnW2bXuPlRd2F0ZE0PUHM13XiccjBSksFMfO1HssP0rZA0XBRDndtB54LAch\nRKAIo17/Xc9noshKaJ5s0qt7BtVtg7Lb4tbfKGz9q9Vgm1EXrgTXdRHCIBJRJkUDA+lC+URNUYig\n68p8xr82T4wQBuaUySTnzlalioEUrlX/AyMIXiA2TVWqUM5zytu3GHwbo7A1uylX7TsLkgAXv4Oi\nR7HHFmhrS/pobMM73213Y0QEXfC8F1SXP5MpmnPXS9Mqv2grHdf/+rDDKT3ousoYvRlntYzEq8Fr\nkvX29pcEucGshPqCiIdaddVKKG79i9lOcA1WZeRKap0ilxuqn0ApdF2npWUwxUxKAoKAKHyGqoTi\nfYaVG4qaphVMappRqiiHEKJA5fKzKsrLE+qcZMlnV7tOvGfdyvwlrLRvIzp+/GgymVzF+W47d+5k\n584uJk6cUmkwdd2oJQEG6O7u5nOfu5577/0l0XzTtBGMiKAbj0eIxczALr+6qeuhacnCBa0033pV\n9kB9mYV6XUuLmjZczfC81rGDmmSVWQnlQaQ2PczjwwpB04KJvwbrp2h5XfJYLEoy6XFHS0sT9QZi\nRWGLE42aDAykS4J/JQQ1i/zMjvKGohDqPNTk6HJh9dARi6naeSajsv9aqFwnDm7YNau8MBx0MUVj\nC57v9tZbb/Ld7/473d3dzJo1mzlz5nLNNTcwevSYht+3mgQY4KWXXuDOO79PV1fXkM4PRkjQzWat\nijdVI3UvTROFMey1zMmr0dX8UNOGTaSE/v6BUIqboGPX0ySrFUQ8epg/EDuOg2maGIZBKhUuWNUD\nIVSpwpPuBlG0/DLieDyWN3ZhUGmi0pazmaWKoM/Qy/5dV2JZFqZpMHp0R1kduw4KWxn82flQWSFB\ngVhREZOALNwfQ6kT7w6Orn++23HHncjPf34CAwNp1qxZw9q1q4fcVKsmAQYVE7773f/ghhuuHtL7\nwAgJuo4j/YydEtRzEXl+BkAdY9irH98zEveoaslknPDbOn+G0hzZbjA9TORr1ioYeufklUAaFUyU\nI0i6G4SSCQWuGiyp+UoTqvanglJpNgzJZAwp5ZCDVRBUKSGOpumB2f9QKWxCkM/OI6Gz83rhPZAy\nGfXA80pjYZkTweturgQ4bP22tbWNo446pu5pvEGoNXr92GNPGPJ7eBgRQXeoKA2MadraEnXwF4Op\nK/7GWzlVLXxzjEK9UznpN5+RABTI7rZt093dm288hRFMhAvE1aS71WA+8RjGa68BAuv448l96IyS\nGqy/I55MlrISotFIIcg1o6HoF1Ck08ECisYobOqz9OTHfk5vM1HMnoMfSEHMCSitE1cKxHuLReRQ\nEGb0erOwXwTdIOEAgGnq+WGV5VSteuwgS19TyXehuJbwF5TrukSjiokxFA5sJVQLhtUy4rDKNeV1\nHMc0zbpLFfqK5Rgvv4LI2z+azz2HO21aQeUF6mGk6xrRqBqDk0pl8mssGuskk6WsBPWgqIOVYBq0\ntCQaFlDUcmFTBuXqNlRdercw3LFZ7JNEIk4s1lj2HKZhF4mYu53GptbVpC4a1SXAzcZ+EnRLg2jp\nhIUsllVO1Qrfka3UeCv3XSh/fTV4pYSBgQy5XK4KBzacGUk5ik2s+uq2lZRrum4MajR5xjq5nFVX\ndutB7NxRCLgAwtAR27dDPuh6wdBxSlkVao0WlhXMSvC2/bUaiv5GX7NZCV75RNd1dF0vfAfVKGz1\nPiz8n5Fl2U3Nnr3rvcjcEPT2DuTFMvUp7MqxN0qATznl9Ka+l6j2RWzf3rfPkOOq7QRaWxOkUhmk\nxDfSpzJVy3t9mAvca7pJCdlsbWVaIqGUW0HvHVa2WxQjqKzT80otpYYFmVaXNrEqmcYMBV6TyXFc\nLMsubK/LJcTVvBwAxNatxBYvKpRTJILMpz+DGDOmKcHQn7V7n6WXtYN6MCuGSe1pzPXCKyV4nNtK\nQcb/sPDWWovC5v07b7LEcNDYoFgbrnYdNVInVgo2IxQbRNMie60qbezY1ooL2y+CbktLHCnBMLSq\nWaj/9ZlMrmZ25jXehBDs2hWu8ZZIRLHt0jHWYYNtNZTenIODnMc3zuUsUql007MJz9JR0zQGBgbf\n6P6MuNIaywOIWLuGyMsvA5A78STi8+fmHxiZwpTdZsLLDKWUOI6Xidb3sKiGSpzbeo/hf9iWf44i\n7zPilVuaDV3XCsyH/v5U3c3KWoHYy5z7+lKVD1JYS+Nc2eHGfh10Y7FIYcKCl+3WQjIZzxuZB99c\nnnrGdV1SqSxtbQl6esLxNL1/5wV+f5Os2fDqmtFoMSMI6xwWFo1YOpavsfxh4S+f2LZT2OpblkMq\nFc4AqB5omiCZrJwZBu0s6pU5F1kDOVKp5mfP3g7DM6gv/RyHRmHz4LmlpVLpkF4j4aEaVzqtrS2k\nUunCA6NaaWJfDbojpqZbzmn1j0vP5ZSUMOwFV+mLrmQk3kgNOGgmWTOhMttYIZB4WZUXPAY7h9XH\nSIDm8GGDmoNekDNNk0RCCTTUmpTzWDMbip5tZDVbx8prLI5OV4HYLfkcbdupyRpoBioFwyAKm2rs\nhaOw+c+1pSWZr5837sZWDS0tCSKRSF6VaOEN3ayksNuXMWKCroegcemev0FYBEuB1Y0VbCTu8Wlr\nXxCuK/MiCVm48JvpkeDPPNPpzKBA4hlRF18f3AirFoiDpivUDcchL+kK+JVLNKoUSCqQZJtiquNH\n8Rzqkzd7KAbiSkFOZc7ea72RP2qUUV1vVfUcPGZF0ENvKBQ2z4Y0kYiXBMNmw9/s6+kpPYdqCjsp\n985abhiMmKDr0b9g8Dib+mksKogqRkIE0zQCx7uXH7+W4QfI/Nosn0eCv0tdDHKNZBPFzDM817Oo\n9CoNxN6NWU4NU11rMaQtpvnIwxhvvAGawDrueOwzziz8Tn0mcXK50nOolhEXO/61A7G/lNBoXbUS\nvCAnpUkkEsk3VrOFYJxI1C+YCIK/Nlxvo6wWhc3bHXnv4zgOqVS6qVRFdWxIJhOYpkl//0DIc5CA\n1nS62O7GiKnptrXFAv1fQZUaPN5sGMRikULtLpezyGSyVbOTWmwHv91iEDySvz+IgGfwUdt/wJ95\nDgykh1ynLYdiPSiup1emCUO7CoK+bCmRX/8KkS/CS9sh+8lPoc2ZXeAMDwykGr7JyxkJ/kAshMg/\nQAc3mbxVD+VW9lOo+vsrn4M/21RrrJxtlsN7KA1XbdjPfMhkcvkHsN4UCpsHld0m803dVMiyHKhv\np0hL25uxX9R0+/szFR2HKqnGghCJmPmpDWqKbbipDcGZdFglWZDtnT8QB/sPKDcuz4w7lWpu1ubB\nL90tz55r+TgEOZuJrq5CwAU1ZSE50IeRb6AMVfoatO2PxSLE8yN6XFcZrkci6gFi2Q6/BV4XAg3J\niZbDaQGm47VQVKzVZlaEzTb937eUbt6iVLBrV3/TH6xQGtCD6tuV+c7hmrOlGXr47FZKL9juu9mt\nHyMm6FaDV5+qBr86LZvNoml66C1+eVBvRpMsOBD7zbgTedmrLPBhPSVTM5pzYaS7tVVrpc5mluVg\nL1gAzz8PKJmlETHJzp1LT8+uptU6PZSWEkprkt6Wf4lpsMQ0aMl/li9HXObncky0wtWIh6pY81Di\nN1FYv5YvnUQLZvnKNzleEuSG2hPwZ+jVAnq9LmweY6LIQEmQy4VzTFPvB6Czr2S3YbEfBd1KtJOi\nOs0zEjdNo6KBTuXjN4dvWw1qFIrKxLPZXEH26lne+Rsj/rJE0LiYShiKdBdqBWKD6LSpmJ+5AfH8\n80ggd9LJWMkWRD6baxY8VoJn7FIOr/66yXFxXJc0qDqhJtihG8yOVDdeLxUgpEsUcM2CpmkkEnEc\nx6G7e1dB5VdLuVZPIC6KHBrjPgcFYiidJpJIeFQ2t2CkVJ3CNvKyWz/226CraSLvVqWTTudKMox6\nG29SynyW6eI41rAE3KLSyylhDEgpC5Z3Hvw1w+CpDcFZnLdFzmSydHfvatravRvTcRwMI4GcOZOB\nCRNxXZXtRg090COhkSzOX98Ow0qY4zi8KI085c9FsyVT0lm8sw+iXXnXh2XZ9PWlcJzhMi43B2Xo\nwRMYSrf95Z9l0BQMj8ompWyIvVELii6nEYkUucmVpok4jsNzz/0Zx3GZMWM27e2djLTs1o8RE3Sr\nbU1LHZHIz/kyyGatQEZCPUFXCSQyxGJmXmKsaodhm2C1oOt6wUErbKc6qGYYfMEXO+ce/3U4bkAo\nDej+zLOS6Xols5pKgbhaoKqGSVJyWTbLK6aJkHCqZdHq+72fdlUsucgCBcyTJKuHWjHA1cML98Or\nq2azudAll+rb/sEG9iDQdW3YlH1eWUfXdXp7i6Wp4GkiKkFYt24dTzzxR959913a2to4/PAj+Kd/\n+pe9VuY7FIwY9oLim1b6naCtLUEmYxGLmeRyNplMrmIg1DS1deztDSbLQ3Ulmb8p4mVJipdbuuWv\ndkN5QUQNgWy+AgiKlo6apuhuRcewoUte/e/hjfsZGEjXHdAH+w8MptipuXjRYZO+hvG5LWUkGHVT\nw8IyH4aC6jLn5qgUi8248N+Fn5ngupIPPtjI9u3bmuKTu6ewX8iAqwXdSERZ6KlZTNmazQ4vSO/a\nNTjoNtok848b8W7KSlv+YlaYI51ON73B5B9lUx7QK3s41KdY888OC/JiGOr6VQZnEo2aBY50M7jO\n5VAPjUTBs6Ke7708EOu67qOGFYOcYlc0XletBfXQSBCJDN4F1PLE8FMCq8H/0FAllzCBe+TWbvcL\nylgQ/LJdoOZMMg9B5YWhNsn840Y8BG35vdcqFzSr6QG3lnQ3WIRQqljTtOr8XE+WOlxBBBT3WhHr\nU/mtfmmDKWiyRD2BuDSI1G9NCZXKPMVAnEwqQQdQCITNZKBA6UOjXPEFweIYKG2E1VIANtKMG6nM\nhDAYMUHXfy0FGYm3tyfrMCYvolljcoLg1bi8BpPjOKTT2cKWurU1OSRvBD+GIt0No1gTQsN1HTRN\nx7btYeOS+o1j/DXPWlxnNXooXCAuehnUb+BTC47j4rpWgePa1zeQ//7DSXPDws+u6OsbqIvBArX9\nJvxJgjdI0rKcEB4kIze7DYsRU14AMM3KRuJtbQn6+zOha4rt7S309ioC93CwESA8Pcu/RTXNUiWY\nZVXv8vubPc2WvXpQnXDV7PMaTEG116Fs+ZXpSqIwqr1R45hq6j/XlYVMs5rP7VAQtlyhMmK/sq4R\n1drw1LihlJLnOG5A2czJc7Nt+vr6icfj+5yqbCjYL2q6mibo7EyQzVqBTad6jMldV5JIRIhETITQ\nyuquzakVetlUIzdGmOaS49hEozFiscgw1gr9to6Dm33+dZqm+j+UrtOy7KoZXKOshHpgGFqh264a\nTJpv2z10BgqUD7UcaKhcMbhBawwyTvJsPJXXbfN3Gn4/3b6+VODD3l9CWb58Oddffx2dnaOYM+dg\n5s49hLPOOodJkyY3fW17E/aLoAtgmpW3NmGMyb1Sgp+kXx7gPGVQo5SwoqzWbqo3rNdcMk215fdq\nhR6VqBmBww8/tUn5FIetlQ7ONCsFOH/9WWWFTVl6CfzTcf0Pv2KAq73OsO8xHNM6glRrriub+sDw\n4DV462HTSKmmdW/cuJEVK1awYsW7HHfcCYVx5yMV+03Q1XUq1lyTyRi5XLAhTr1NsmLgCKaEecHY\nD8Mw8uPXh2boUg1+6a63PR4qda3ye3jDPId+HkEZnKoNKuFHLmc19YEBjZUrgqmAlQOxruu0tiby\ng0+Ds8KhIug9aq+z6N1R/3uE9SOBYhlh/6vdHgi6DN+YnOJ7D+ZpemobTdPypjSpmqOCGoGqDSfy\nY2Cqb8ErrbOWWs2/zW+GMU0Q/O+RTqv6u5e9l9Y0Gxcg+EsijUzHLUclTrb3Xor2F34nUA/qmfJb\nKXMvZ6FUairW81ntT7XbSjgQdFEDKV2XwoUznGNyoMiNjEZNHMfN8yH1QUFjqJME/EqvRpsmfuqa\nd2P6R+aoMefDxxsG5QSWSMSrlhIafWB48Eo7jXBuw8JrlHmsFG+O2VDZCH74TXb6+1MNHycoEEPj\nTcX9Pbv140DQRd3UAKlUdliDLZQacZcPgfTXhj3aUCONuqEqvWrB8xrw7ASDmAjNGD3jL4k00vwJ\nE4iVM9fwqr1qzVnzO8QNZiOEMzP37wTUewyPyY6nhPR2aVCbhXIguy3FfhN0NS1w+gugsoNEIlqY\nl1bveJcwUFzYOFKGr3dW7vAHN+o8epbqUKfr5l+GQSWaWdADo2DZWKdBjV8VV7J1dRwq4hj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rvtDqZNOyjgt9Voa+GOX4nbW95MKp8c0dJi5F9XGogrBVFvpI16n/DjyMPA36jLZIrZbTqdRQhB\nLBajpSVYUVc8Buxt2a0f1VgJbW3tzJt3CKNHjwHg8MOPYtWqlQeC7khENfULwEsvvcCdd36frq6u\nPbjKfRtCiAoBF2rR1mqxJeoZNVN9UGSp6qsYhFVg84schotDDKUTI4LEFOWKumeeeZo77riDuXPn\ncfDB85k//1BmzZqNYex9QbcaK2Hu3Pm8994aenp6aGlpYenSd7jooov34Gr3PEZs0K2lftE0wXe/\n+x/ccMPVe2J5+ylqm8CvXr2S22//Nueddx6XXHJpw/XaWvXhWCxREJzkclZ+HLnW1PowlA6GrCam\nKBdHLFhwOH/3d19h6dKlLFu2lAcffIArr/wUF1yw9wWs0047g1deeYmbbrq+YFLzy1/eV2Al3Hjj\n5/nrv74FgDPPPLskKK9b9x7f/va/MjAwQDQa5W/+5u+ZM2funjqV3YIRG3RrqV+OPfaEPbW0AyhB\nMRA/9ND9LFp0FzfeeDPnn38Rtu1lwM2rDztODk2LomkaqVQay7IL9WHPnrG0Pty4K1g92XoRqnZr\nGBEOPngBBx+8gEv20PTwWiW6737327z99lsF+9LvfOeOAhVx+vSDCq87++yPcPbZHwl8j29+82tc\nffV1nHTSKbz22it87Wv/l3vv/a/hOqW9AiM26IZRv4RBrQvv/vt/zhNPPAbAiSeezPXXf3boi99P\nccghh3Lvvb8s1P+KCK4P1xuE1dTiBFKWTqWoXh+urFCrBDUPLYmmiSGMztnzZYRaJboVK5Zz++0/\nCC3Z/e///iXPPPMk3//+j3n77bf4xjf+mU984srCjnTWrDls3bplWM5lb8KIDbq11C9hUe3C++CD\njTz22CP85CeLEULw+c9/mtNOO4PZs+c081T2G8yfv6DCbxqbTeeHJ3IYGEiXTIQoR636cCIR803r\nHTxHrZHBkHsrM6Faic51XTZu3MC3vvV1urt3cv75H+OCCz5W9XiXXXYFf/rTU/zqVw/y4IO/5Ctf\n+SqHHXZE4fc//emdnHbah4blXPYmjNigW6vOFBbVLrzx4ydw223fL9QGbdsmEok090QOoAKCArE7\nKBt+6603ueuuO/nhD/+DdDo7DFaSxTlqUqpsPJ3O1Kkq23uyWz+qlegymTSXXno5V155Fa7r8IUv\n3MS8eYdUTTiEEPzDP/z//OVfXsEll3yiEHCllPzwh99j2bJ3uOOOHw/7ee1pjNigq2kaX/7yV0p+\n5q8zeXjwwd9VPU61C88wDDo6OgoXzZw5c/drKsyeRzFoua7L7bd/i+eee5Yvf/nvkFIvSJKbMZuu\n2PjKFSTJ2WwOx3ExDIO2tihCFP0lBteH987s1o9qJbpoNMbll3+SWEzZjR599DGsXr2y5i5vy5bN\nJBJJVq5cjpQSx3H42te+yo4d27njjh9XkaePHIzYoNss1KoNZ7NZvvGNfyGRSHDrrX9f9Vi16sMP\nPfQADz/8e4SAa6/9DCeffGrzT2g/gW3bTJo0mf/8zwfKbuShzabzQ9M0WlsTgCib9hssjNC0GFde\neSWjR4/h4IPnMX/+AubNW0Bra+sQznT4UK1Et2HDer761a9wzz33IaXk7bff4txzL6h6vFQqxbe+\n9XW++c3bWbToLn71qwfZsGE9qdQAt9/+g/1ml3jAe6EGnn76jzz33LMFXfmiRXdx2213ACoA33rr\nFzjqqGO46qprax6rmka9p6eHW275LIsX/4JcLstVV13OQw/9fq+c/zTyIPEH4DCBuNpgyGrvs23b\nDpYuXcKSJUt5992ledPu+4a4/uFBrXllP//5vTz11B8xDINzz/0oF198WdXjfec7/4Zpmvyf/3Mr\nW7Zs5vLLVQ140qTJxGLxwusWL/7FsJ7X7sABw5shoNqF5zgu//zP/1gyAvqmm27h0EMPCzzW979/\nO/PnLyjQZy6++Dx+/euHC7/3yhYbNqznH//xy/zsZ/cP78kdQAUEm/wAvP/+Wp544nH++q9vrctw\nZ1+ZVeZ/zZe//CVOPfW0msH0AAbjgOHNEFCrNvzkk8+HPlYt7rBhGDz00P3cffdPuOyyK4a28AMY\nAgY36Wzb4r77FvPgg/fzxS9+iV271Ojv2mWJva92W4sKBnDXXT+it3fXHlrhyMbecRXsJwjDHb70\n0iv4zW8e4a233uD111+teCzXdfn2t/+VG2+8jltu+SwbN24IfM2tt36RX//6weadxH6KLVu28P77\n73P33ffx4Q9fgMpX9HyDTkNKgZSUsCfU3zVAZ2+61WqpNZ966gmEECN2MOSext5zJewHWLjwcF58\n8TmAQY2J9evX8ZWvfLkQiE3TrFrP9WcrN930BX7wg38f9JoD2UrzMGXKVL761a+VTTXwZ7A6XnBV\ngVj4fr531eUr7bgA1q5dzeOPP8qnP33TnlreiMeB8sJuRC3u8OzZc7jxxusKWcaRRx5d8VgHspW9\nEXvHqPNaqLbjeuSRP7B9+za++MWb2LJlM4ZhMmHCpAPXURNxIOjuRtSqD19//WdDy4ir1Ye9bOVr\nX/smixaN3FHWB9AYqlHBbv5/7Z1PTFx1EMc/NiRQQArhIjHRsLYM2iiJMcY2hOrBxpoQsQeD4VAa\nyJLSphqjB9OLJ8RKUeKGRmItFw0pmtWmqZ68VarEtEBLHKGhLSm9eNhq2gTDHw+7xSewb3fpg31v\nmc9pX96PyZBNvpk3++Y77W8tfT516nPKy8tNcD3GRDegWLVirBWvpjWNtWGiG1C8rFYydZPq7Oze\nFJNDQSPT4RvnU9dq05otLW0bkfamw0Q3oHhZrXjtJmVkB7fvMRaLEY1+87/hm927a234JguY6AaU\ndL0l0qlWvHaTMrKD2/dYWlpKf//X5OXlcfv2DMXFxSa4WcJEN8c4d+47RkYuc+zYB2n/jdduUkZ2\nsOGbYGDv6eYIs7OznDz5GT093akPLyNdN6nCwqIlNyk3Ug1uDA1dIBxuJhxupqurc012i8ZKvBy+\nMdYPE90AMjg4wJEjYRYX436xjY2vMzx8kcXFBdrbj2Ycz21oY3r6JocOtTI/H7cnHB0doaqq2jWe\n2+DGvXt36e3t4fjxT+nr66eiooJYLJZxzsZKvBy+MdYPay8EkGQO/LW1ezh/3t0feDVS/Si3d+8r\ntLUdXHKTCoWecI3n1lscGxslFNpOJPIJMzO3qK9voKysLOOcjZV4OXxjrB8mugEkmQP/Wkn1o1xT\n0wGamg6kHc+tt3jnToxLl37j9Omv2Lq1kMOHW9m582kzf3ch0z19yV4Fy2T4xlg/THQDynIHfj89\nKrr1FktKtlFd/dTS8smammeZmPgjqei6Cc7EhNLTc2Lp7Pj4FTo6unJuCMT29OUW1tMNIE4H/vz8\nfKJRf7mIufUWRZ5kauoasViMubk5rl4do7KyMmkst/7wjh1CJNJHJNLH/v1vUFf3Us4JLqS/p+/+\nE8Vm2cAQVFxNzA1/IiK9wD+q+raIPA78AuxS1SkRaQZeVNXmLOa3BegFniHuAHMQeBWYVNWzItII\nvJc4fkZVP3KJ1Q38qqoDietbqvrosjNFwDBQp6p/ev4PZRkR+QL4VlV/SFzfBEKqOuc48xDwMfCw\nqtoomY+x9kIAUdV2x+cbwCOO636gf+Oz+g9VXQCWewP+7rg/AAykGa4EcPpTzotInlNwgBZgMBcF\nN8FfgHOR2pZlglsAfAn8DbRj+BoTXcPvuApOgiYgrZ0yjiq8hvgGyVZVnXTcfxd4E1gAOlQ1+gC5\ne8UFoB44IyIvAGP3byQq3O+Bn9yeGAz/YKJr+J2kggMgItuAfFVduTpjdRqAAlXdlYh3AngtEasU\nOApsB4qAy4AfRDcKvCwiP5No14jIO8AkcZf0PUC+iOxLnH9fVYeyk6qRChNdw+8kFRxVPQtUAdcz\niFcL/AigqhdF5DnHvbvADeKCW0S82s06qdo1QMEGpmM8ICa6hq9Joz88TLx6TZdUPeJpYJx4Bflh\n5hkbhjv2ypix2XDrEe8DKoBK4DGgQUSe3+D8jBznX6WuaAS3LK01AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ade7d3278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gumpy.plot.PCA(\"3D\", features, split_features[0], split_features[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classification with normal split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "results, clf = gumpy.classify('LDA', X_train, Y_train, X_test, Y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification results on test set:\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.73      0.63      0.68        38\n",
      "          1       0.56      0.67      0.61        27\n",
      "\n",
      "avg / total       0.66      0.65      0.65        65\n",
      "\n",
      "Accuracy:  64.61538461538461\n"
     ]
    }
   ],
   "source": [
    "print(\"Classification results on test set:\")\n",
    "print(results)\n",
    "print(\"Accuracy: \", results.accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confusion Matrix\n",
    "One of the ideas behind ``gumpy`` is to provide users the means to quickly examine their data. Therefore, gumpy provides mostly wraps existing libraries. This allows to show data with ease, and still be able to modify the plots in any way the underlying libraries allow:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WQBhqQRgRyUOtVsv8yMLM3mtmCwcsO9jMbs+yvloIIiXK8y9yrP58GPB8w7I+4ONk7J2o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\nsKAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ade85a828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gumpy.plot.confusion_matrix(Y_test, results.pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Voting Classifier with feature selection\n",
    "`gumpy` allows to automatically use all classifiers that are known in `gumpy.classification.available_classifiers` in a voting classifier (for more details see `sklearn.ensemble.VotingClassifier`). In case you developed a custom classifier and registered it using the `@register_classifier` decorator, it will be automatically used as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification result for hard voting classifier\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.73      0.63      0.68        38\n",
      "          1       0.56      0.67      0.61        27\n",
      "\n",
      "avg / total       0.66      0.65      0.65        65\n",
      "\n",
      "Accuracy:  64.61538461538461\n"
     ]
    }
   ],
   "source": [
    "result, _ = gumpy.classification.vote(X_train, Y_train, X_test, Y_test, 'hard', False, (6,12))\n",
    "print(\"Classification result for hard voting classifier\")\n",
    "print(result)\n",
    "print(\"Accuracy: \", result.accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, we can plot the confusion matrix to have a look at the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IEo+IVKTg6yGsNPszsI+7L4j3xwFLU+PJ/xFEpCiNRiPzLY27Xwm83PT4zwBmti3hYsln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\nJJQQRCShhCAiif8HkndXBKLOTVIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ade702048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gumpy.plot.confusion_matrix(result.pred, Y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because `gumpy.classification.vote` uses `sklearn.ensemble.VotingClassifier` as backend, it is possible to specify different methods for the voting such as 'soft'. In addition, the method can be told to first extract features via `mlxtend.feature_selection.SequentialFeatureSelector` before classification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Done  30 out of  30 | elapsed:   35.8s finished\n",
      "\n",
      "[2018-02-16 13:51:47] Features: 1/12 -- score: 0.598324786325[Parallel(n_jobs=-1)]: Done  29 out of  29 | elapsed:   39.5s finished\n",
      "[Parallel(n_jobs=-1)]: Done   1 out of   1 | elapsed:    4.1s finished\n",
      "\n",
      "[2018-02-16 13:52:31] Features: 2/12 -- score: 0.663897435897[Parallel(n_jobs=-1)]: Done  28 out of  28 | elapsed:   35.9s finished\n",
      "[Parallel(n_jobs=-1)]: Done   2 out of   2 | elapsed:    5.0s finished\n",
      "\n",
      "[2018-02-16 13:53:12] Features: 3/12 -- score: 0.66758974359[Parallel(n_jobs=-1)]: Done  27 out of  27 | elapsed:   35.8s finished\n",
      "[Parallel(n_jobs=-1)]: Done   3 out of   3 | elapsed:    5.1s finished\n",
      "\n",
      "[2018-02-16 13:53:53] Features: 4/12 -- score: 0.651908831909[Parallel(n_jobs=-1)]: Done  26 out of  26 | elapsed:   35.8s finished\n",
      "[Parallel(n_jobs=-1)]: Done   4 out of   4 | elapsed:    5.3s finished\n",
      "\n",
      "[2018-02-16 13:54:35] Features: 5/12 -- score: 0.660512820513[Parallel(n_jobs=-1)]: Done  25 out of  25 | elapsed:   34.6s finished\n",
      "[Parallel(n_jobs=-1)]: Done   5 out of   5 | elapsed:   10.3s finished\n",
      "\n",
      "[2018-02-16 13:55:20] Features: 6/12 -- score: 0.660062678063[Parallel(n_jobs=-1)]: Done  24 out of  24 | elapsed:   31.5s finished\n",
      "[Parallel(n_jobs=-1)]: Done   3 out of   6 | elapsed:    5.3s remaining:    5.3s\n",
      "[Parallel(n_jobs=-1)]: Done   6 out of   6 | elapsed:   10.3s finished\n",
      "[Parallel(n_jobs=-1)]: Done   5 out of   5 | elapsed:   10.1s finished\n",
      "[Parallel(n_jobs=-1)]: Done   4 out of   4 | elapsed:    5.2s finished\n",
      "\n",
      "[2018-02-16 13:56:18] Features: 5/12 -- score: 0.691612535613[Parallel(n_jobs=-1)]: Done  25 out of  25 | elapsed:   35.2s finished\n",
      "[Parallel(n_jobs=-1)]: Done   5 out of   5 | elapsed:   10.2s finished\n",
      "\n",
      "[2018-02-16 13:57:04] Features: 6/12 -- score: 0.695304843305[Parallel(n_jobs=-1)]: Done  24 out of  24 | elapsed:   31.6s finished\n",
      "[Parallel(n_jobs=-1)]: Done   3 out of   6 | elapsed:    5.2s remaining:    5.2s\n",
      "[Parallel(n_jobs=-1)]: Done   6 out of   6 | elapsed:   10.4s finished\n",
      "\n",
      "[2018-02-16 13:57:46] Features: 7/12 -- score: 0.707447293447[Parallel(n_jobs=-1)]: Done  23 out of  23 | elapsed:   32.4s finished\n",
      "[Parallel(n_jobs=-1)]: Done   6 out of   8 | elapsed:   10.7s remaining:    3.6s\n",
      "[Parallel(n_jobs=-1)]: Done   8 out of   8 | elapsed:   11.0s finished\n",
      "\n",
      "[2018-02-16 13:58:30] Features: 8/12 -- score: 0.696051282051[Parallel(n_jobs=-1)]: Done  22 out of  22 | elapsed:   32.3s finished\n",
      "[Parallel(n_jobs=-1)]: Done   6 out of   8 | elapsed:   10.7s remaining:    3.6s\n",
      "[Parallel(n_jobs=-1)]: Done   8 out of   8 | elapsed:   10.7s finished\n",
      "[Parallel(n_jobs=-1)]: Done   4 out of   7 | elapsed:    5.7s remaining:    4.3s\n",
      "[Parallel(n_jobs=-1)]: Done   7 out of   7 | elapsed:   10.7s finished\n",
      "\n",
      "[2018-02-16 13:59:24] Features: 8/12 -- score: 0.69958974359[Parallel(n_jobs=-1)]: Done  22 out of  22 | elapsed:   33.2s finished\n",
      "[Parallel(n_jobs=-1)]: Done   6 out of   8 | elapsed:   10.6s remaining:    3.5s\n",
      "[Parallel(n_jobs=-1)]: Done   8 out of   8 | elapsed:   10.9s finished\n",
      "\n",
      "[2018-02-16 14:00:08] Features: 9/12 -- score: 0.696193732194[Parallel(n_jobs=-1)]: Done  21 out of  21 | elapsed:   32.2s finished\n",
      "[Parallel(n_jobs=-1)]: Done   7 out of   9 | elapsed:   10.6s remaining:    3.0s\n",
      "[Parallel(n_jobs=-1)]: Done   9 out of   9 | elapsed:   15.5s finished\n",
      "\n",
      "[2018-02-16 14:00:56] Features: 10/12 -- score: 0.703458689459[Parallel(n_jobs=-1)]: Done  20 out of  20 | elapsed:   26.9s finished\n",
      "[Parallel(n_jobs=-1)]: Done  10 out of  10 | elapsed:   15.9s finished\n",
      "\n",
      "[2018-02-16 14:01:39] Features: 11/12 -- score: 0.695316239316[Parallel(n_jobs=-1)]: Done  19 out of  19 | elapsed:   28.0s finished\n",
      "[Parallel(n_jobs=-1)]: Done  11 out of  11 | elapsed:   16.5s finished\n",
      "\n",
      "[2018-02-16 14:02:24] Features: 12/12 -- score: 0.706558404558"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification result for soft voting classifier\n",
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.73      0.63      0.68        38\n",
      "          1       0.56      0.67      0.61        27\n",
      "\n",
      "avg / total       0.66      0.65      0.65        65\n",
      "\n",
      "Accuracy:  64.61538461538461\n"
     ]
    }
   ],
   "source": [
    "result, _ = gumpy.classification.vote(X_train, Y_train, X_test, Y_test, 'soft', True, (6,12))\n",
    "print(\"Classification result for soft voting classifier\")\n",
    "print(result)\n",
    "print(\"Accuracy: \", result.accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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m7zWz+QOWHWhmt2dZXy0EkRLl+Rc5Vn8+BHihadlU4JNk7J2ohSBSopzvh7BG9Wcz2wA4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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b380fe748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gumpy.plot.confusion_matrix(result.pred, Y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python3.5",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
